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2D Object Detection: A Survey
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inferredcites →https://doi.org/10.1002/nav.3800020109openalex-snapshot
The Hungarian method for the assignment problem
inferredcites →https://doi.org/10.1007/11736790_8openalex-snapshot
The 2005 PASCAL Visual Object Classes Challenge
inferredcites →https://doi.org/10.1007/3-540-59119-2_166openalex-snapshot
A desicion-theoretic generalization of on-line learning and an application to boosting
inferredcites →https://doi.org/10.1007/978-1-4471-4929-3_11openalex-snapshot
Class-Specific Hough Forests for Object Detection
inferredcites →https://doi.org/10.1007/978-1-4899-7687-1_79openalex-snapshot
Empirical Risk Minimization
inferredcites →https://doi.org/10.1007/978-3-030-01219-9_39openalex-snapshot
Occlusion-Aware R-CNN: Detecting Pedestrians in a Crowd
inferredcites →https://doi.org/10.1007/978-3-030-01228-1_15openalex-snapshot
Parallel Feature Pyramid Network for Object Detection
inferredcites →https://doi.org/10.1007/978-3-030-01231-1_29openalex-snapshot
Simple Baselines for Human Pose Estimation and Tracking
inferredcites →https://doi.org/10.1007/978-3-030-01234-2_1openalex-snapshot
CBAM: Convolutional Block Attention Module
inferredcites →https://doi.org/10.1007/978-3-030-01234-2_31openalex-snapshot
Localization Recall Precision (LRP): A New Performance Metric for Object Detection
inferredcites →https://doi.org/10.1007/978-3-030-01252-6_24openalex-snapshot
Receptive Field Block Net for Accurate and Fast Object Detection
inferredcites →https://doi.org/10.1007/978-3-030-01252-6_49openalex-snapshot
Deep Regionlets for Object Detection
inferredcites →https://doi.org/10.1007/978-3-030-01264-9_45openalex-snapshot
CornerNet: Detecting Objects as Paired Keypoints
inferredcites →https://doi.org/10.1007/978-3-030-01264-9_48openalex-snapshot
Acquisition of Localization Confidence for Accurate Object Detection
inferredcites →https://doi.org/10.1007/978-3-030-01267-0_28openalex-snapshot
Revisiting RCNN: On Awakening the Classification Power of Faster RCNN
inferredcites →https://doi.org/10.1007/978-3-030-58452-8_13openalex-snapshot
End-to-End Object Detection with Transformers
inferredcites →https://doi.org/10.1007/978-3-030-58452-8_32openalex-snapshot
BorderDet: Border Feature for Dense Object Detection
inferredcites →https://doi.org/10.1007/978-3-030-58536-5_24openalex-snapshot
RAFT: Recurrent All-Pairs Field Transforms for Optical Flow
inferredcites →https://doi.org/10.1007/978-3-030-58545-7_6openalex-snapshot
Soft Anchor-Point Object Detection
inferredcites →https://doi.org/10.1007/978-3-030-58580-8_24openalex-snapshot
Corner Proposal Network for Anchor-Free, Two-Stage Object Detection
inferredcites →https://doi.org/10.1007/978-3-031-20077-9_17openalex-snapshot
Exploring Plain Vision Transformer Backbones for Object Detection
inferredcites →https://doi.org/10.1007/978-3-031-20077-9_21openalex-snapshot
Detecting Twenty-Thousand Classes Using Image-Level Supervision
inferredcites →https://doi.org/10.1007/978-3-031-20077-9_41openalex-snapshot
PromptDet: Towards Open-Vocabulary Detection Using Uncurated Images
inferredcites →https://doi.org/10.1007/978-3-031-20077-9_7openalex-snapshot
Open-Vocabulary DETR with Conditional Matching
inferredcites →https://doi.org/10.1007/978-3-031-20080-9_16openalex-snapshot
Open Vocabulary Object Detection with Pseudo Bounding-Box Labels
inferredcites →https://doi.org/10.1007/978-3-031-20080-9_23openalex-snapshot
ObjectBox: From Centers to Boxes for Anchor-Free Object Detection
inferredcites →https://doi.org/10.1007/978-3-031-20080-9_41openalex-snapshot
A Simple Single-Scale Vision Transformer for Object Detection and Instance Segmentation
inferredcites →https://doi.org/10.1007/978-3-031-72751-1_1openalex-snapshot
YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information
inferredcites →https://doi.org/10.1007/978-3-319-10584-0_20openalex-snapshot
Simultaneous Detection and Segmentation
inferredcites →https://doi.org/10.1007/978-3-319-10590-1_5openalex-snapshot
30Hz Object Detection with DPM V5
inferredcites →https://doi.org/10.1007/978-3-319-10602-1_20openalex-snapshot
Towards Unified Object Detection and Semantic Segmentation
inferredcites →https://doi.org/10.1007/978-3-319-10602-1_26openalex-snapshot
Edge Boxes: Locating Object Proposals from Edges
inferredcites →https://doi.org/10.1007/978-3-319-10602-1_48openalex-snapshot
Microsoft COCO: Common Objects in Context
inferredcites →https://doi.org/10.1007/978-3-319-24574-4_28openalex-snapshot
U-Net: Convolutional Networks for Biomedical Image Segmentation
inferredcites →https://doi.org/10.1007/978-3-319-46448-0_2openalex-snapshot
SSD: Single Shot MultiBox Detector
inferredcites →https://doi.org/10.1007/978-3-319-46448-0_20openalex-snapshot
Contextual Priming and Feedback for Faster R-CNN
inferredcites →https://doi.org/10.1007/978-3-319-46448-0_5openalex-snapshot
Learning to Refine Object Segments
inferredcites →https://doi.org/10.1007/978-3-319-46454-1openalex-snapshot
Computer Vision – ECCV 2016
inferredcites →https://doi.org/10.1007/978-3-319-46466-4_32openalex-snapshot
Instance-Sensitive Fully Convolutional Networks
inferredcites →https://doi.org/10.1007/978-3-319-46478-7_22openalex-snapshot
Gated Bi-directional CNN for Object Detection
inferredcites →https://doi.org/10.1007/978-3-319-46493-0_22openalex-snapshot
A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection
inferredcites →https://doi.org/10.1007/978-3-319-54193-8_14openalex-snapshot
R-CNN for Small Object Detection
inferredcites →https://doi.org/10.1007/978-3-319-58347-1_10openalex-snapshot
Domain-Adversarial Training of Neural Networks
inferredcites →https://doi.org/10.1007/978-3-540-88682-2_2openalex-snapshot
Learning to Localize Objects with Structured Output Regression
inferredcites →https://doi.org/10.1007/978-3-642-33709-3_46openalex-snapshot
Crosstalk Cascades for Frame-Rate Pedestrian Detection
inferredcites →https://doi.org/10.1007/978-3-642-33718-5_60openalex-snapshot
Object Detection Using Strongly-Supervised Deformable Part Models
inferredcites →https://doi.org/10.1007/bfb0054769openalex-snapshot
A probabilistic approach to object recognition using local photometry and global geometry
inferredcites →https://doi.org/10.1007/s10032-019-00335-yopenalex-snapshot
An anchor-free region proposal network for Faster R-CNN-based text detection approaches
inferredcites →https://doi.org/10.1007/s10462-024-10877-1openalex-snapshot
A comprehensive survey of deep learning-based lightweight object detection models for edge devices
inferredcites →https://doi.org/10.1007/s11263-006-0033-9openalex-snapshot
POP: Patchwork of Parts Models for Object Recognition
inferredcites →https://doi.org/10.1007/s11263-007-0095-3openalex-snapshot
Robust Object Detection with Interleaved Categorization and Segmentation
inferredcites →https://doi.org/10.1007/s11263-009-0275-4openalex-snapshot
The Pascal Visual Object Classes (VOC) Challenge
inferredcites →https://doi.org/10.1007/s11263-013-0620-5openalex-snapshot
Selective Search for Object Recognition
inferredcites →https://doi.org/10.1007/s11263-013-0667-3openalex-snapshot
Face Alignment by Explicit Shape Regression
inferredcites →https://doi.org/10.1007/s11263-014-0733-5openalex-snapshot
The Pascal Visual Object Classes Challenge: A Retrospective
inferredcites →https://doi.org/10.1007/s11263-015-0816-yopenalex-snapshot
ImageNet Large Scale Visual Recognition Challenge
inferredcites →https://doi.org/10.1007/s41095-022-0274-8openalex-snapshot
PVT v2: Improved baselines with pyramid vision transformer
inferredcites →https://doi.org/10.1016/0025-5564(75)90075-9openalex-snapshot
The main sequence, a tool for studying human eye movements
inferredcites →https://doi.org/10.1016/j.cviu.2019.102827openalex-snapshot
ASSD: Attentive single shot multibox detector
inferredcites →https://doi.org/10.1016/j.neucom.2017.12.070openalex-snapshot
Cascade region proposal and global context for deep object detection
inferredcites →https://doi.org/10.1023/a:1008162616689openalex-snapshot
A Trainable System for Object Detection
inferredcites →https://doi.org/10.1023/a:1011179004708openalex-snapshot
Probabilistic Methods for Finding People
inferredcites →https://doi.org/10.1023/b:visi.0000011202.85607.00openalex-snapshot
Object Detection Using the Statistics of Parts
inferredcites →https://doi.org/10.1023/b:visi.0000013087.49260.fbopenalex-snapshot
Robust Real-Time Face Detection
inferredcites →https://doi.org/10.1023/b:visi.0000029664.99615.94openalex-snapshot
Distinctive Image Features from Scale-Invariant Keypoints
inferredcites →https://doi.org/10.1023/b:visi.0000042934.15159.49openalex-snapshot
Pictorial Structures for Object Recognition
inferredcites →https://doi.org/10.1049/ip-vis:19941301openalex-snapshot
Original approach for the localisation of objects in images
inferredcites →https://doi.org/10.1093/ijl/3.4.235openalex-snapshot
Introduction to WordNet: An On-line Lexical Database *
inferredcites →https://doi.org/10.1109/34.655647openalex-snapshot
Neural network-based face detection
inferredcites →https://doi.org/10.1109/34.655648openalex-snapshot
Example-based learning for view-based human face detection
inferredcites →https://doi.org/10.1109/34.917571openalex-snapshot
Example-based object detection in images by components
inferredcites →https://doi.org/10.1109/3dv.2019.00019openalex-snapshot
IoU Loss for 2D/3D Object Detection
inferredcites →https://doi.org/10.1109/cac48633.2019.8996582openalex-snapshot
Feature Fusion and Enhancement for Single Shot Multibox Detector
inferredcites →https://doi.org/10.1109/cvpr.1997.609310openalex-snapshot
Training support vector machines: an application to face detection
inferredcites →https://doi.org/10.1109/cvpr.1998.698721openalex-snapshot
Rotation Invariant Neural Network-Based Face Detection
inferredcites →https://doi.org/10.1109/cvpr.2000.855895openalex-snapshot
A statistical method for 3D object detection applied to faces and cars
inferredcites →https://doi.org/10.1109/cvpr.2001.990517openalex-snapshot
Rapid object detection using a boosted cascade of simple features
inferredcites →https://doi.org/10.1109/cvpr.2003.1211479openalex-snapshot
Object class recognition by unsupervised scale-invariant learning
inferredcites →https://doi.org/10.1109/cvpr.2004.1315206openalex-snapshot
PCA-SIFT: a more distinctive representation for local image descriptors
inferredcites →https://doi.org/10.1109/cvpr.2005.329openalex-snapshot
Spatial Priors for Part-Based Recognition Using Statistical Models
inferredcites →https://doi.org/10.1109/cvpr.2006.68openalex-snapshot
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
inferredcites →https://doi.org/10.1109/cvpr.2007.383086openalex-snapshot
Semantic Hierarchies for Recognizing Objects and Parts
inferredcites →https://doi.org/10.1109/cvpr.2008.4587586openalex-snapshot
Beyond sliding windows: Object localization by efficient subwindow search
inferredcites →https://doi.org/10.1109/cvpr.2008.4587597openalex-snapshot
A discriminatively trained, multiscale, deformable part model
inferredcites →https://doi.org/10.1109/cvpr.2009.5206848openalex-snapshot
ImageNet: A large-scale hierarchical image database
inferredcites →https://doi.org/10.1109/cvpr.2010.5539906openalex-snapshot
Cascade object detection with deformable part models
inferredcites →https://doi.org/10.1109/cvpr.2011.5995678openalex-snapshot
Boosted local structured HOG-LBP for object localization
inferredcites →https://doi.org/10.1109/cvpr.2013.237openalex-snapshot
Fast, Accurate Detection of 100,000 Object Classes on a Single Machine
inferredcites →https://doi.org/10.1109/cvpr.2013.417openalex-snapshot
Histograms of Sparse Codes for Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2014.276openalex-snapshot
Scalable Object Detection Using Deep Neural Networks
inferredcites →https://doi.org/10.1109/cvpr.2014.320openalex-snapshot
The Fastest Deformable Part Model for Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2014.81openalex-snapshot
Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
inferredcites →https://doi.org/10.1109/cvpr.2015.7298594openalex-snapshot
Going deeper with convolutions
inferredcites →https://doi.org/10.1109/cvpr.2015.7298642openalex-snapshot
Hypercolumns for object segmentation and fine-grained localization
inferredcites →https://doi.org/10.1109/cvpr.2015.7298854openalex-snapshot
DeepID-Net: Deformable deep convolutional neural networks for object detection
inferredcites →https://doi.org/10.1109/cvpr.2015.7298965openalex-snapshot
Fully convolutional networks for semantic segmentation
inferredcites →https://doi.org/10.1109/cvpr.2015.7299025openalex-snapshot
Convolutional feature masking for joint object and stuff segmentation
inferredcites →https://doi.org/10.1109/cvpr.2016.255openalex-snapshot
End-to-End People Detection in Crowded Scenes
inferredcites →https://doi.org/10.1109/cvpr.2016.260openalex-snapshot
G-CNN: An Iterative Grid Based Object Detector
inferredcites →https://doi.org/10.1109/cvpr.2016.308openalex-snapshot
Rethinking the Inception Architecture for Computer Vision
inferredcites →https://doi.org/10.1109/cvpr.2016.314openalex-snapshot
Inside-Outside Net: Detecting Objects in Context with Skip Pooling and Recurrent Neural Networks
inferredcites →https://doi.org/10.1109/cvpr.2016.343openalex-snapshot
Instance-Aware Semantic Segmentation via Multi-task Network Cascades
inferredcites →https://doi.org/10.1109/cvpr.2016.89openalex-snapshot
Training Region-Based Object Detectors with Online Hard Example Mining
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/cvpr.2016.91openalex-snapshot
You Only Look Once: Unified, Real-Time Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2016.92openalex-snapshot
LocNet: Improving Localization Accuracy for Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2016.98openalex-snapshot
HyperNet: Towards Accurate Region Proposal Generation and Joint Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2017.106openalex-snapshot
Feature Pyramid Networks for Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2017.143openalex-snapshot
Realtime Multi-person 2D Pose Estimation Using Part Affinity Fields
inferredcites →https://doi.org/10.1109/cvpr.2017.195openalex-snapshot
Xception: Deep Learning with Depthwise Separable Convolutions
inferredcites →https://doi.org/10.1109/cvpr.2017.324openalex-snapshot
A-Fast-RCNN: Hard Positive Generation via Adversary for Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2017.351openalex-snapshot
Speed/Accuracy Trade-Offs for Modern Convolutional Object Detectors
inferredcites →https://doi.org/10.1109/cvpr.2017.472openalex-snapshot
Fully Convolutional Instance-Aware Semantic Segmentation
inferredcites →https://doi.org/10.1109/cvpr.2017.557openalex-snapshot
RON: Reverse Connection with Objectness Prior Networks for Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2017.634openalex-snapshot
Aggregated Residual Transformations for Deep Neural Networks
inferredcites →https://doi.org/10.1109/cvpr.2017.690openalex-snapshot
YOLO9000: Better, Faster, Stronger
inferredcites →https://doi.org/10.1109/cvpr.2017.87openalex-snapshot
Accurate Single Stage Detector Using Recurrent Rolling Convolution
inferredcites →https://doi.org/10.1109/cvpr.2018.00062openalex-snapshot
Scale-Transferrable Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2018.00352openalex-snapshot
Domain Adaptive Faster R-CNN for Object Detection in the Wild
inferredcites →https://doi.org/10.1109/cvpr.2018.00377openalex-snapshot
An Analysis of Scale Invariance in Object Detection - SNIP
inferredcites →https://doi.org/10.1109/cvpr.2018.00378openalex-snapshot
Relation Networks for Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2018.00392openalex-snapshot
Maximum Classifier Discrepancy for Unsupervised Domain Adaptation
inferredcites →https://doi.org/10.1109/cvpr.2018.00435openalex-snapshot
Feature Selective Networks for Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2018.00442openalex-snapshot
Single-Shot Refinement Neural Network for Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2018.00525openalex-snapshot
Cross-Domain Weakly-Supervised Object Detection Through Progressive Domain Adaptation
inferredcites →https://doi.org/10.1109/cvpr.2018.00609openalex-snapshot
Single-Shot Object Detection with Enriched Semantics
inferredcites →https://doi.org/10.1109/cvpr.2018.00644openalex-snapshot
Cascade R-CNN: Delving Into High Quality Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2018.00647openalex-snapshot
MegDet: A Large Mini-Batch Object Detector
inferredcites →https://doi.org/10.1109/cvpr.2018.00742openalex-snapshot
Cascaded Pyramid Network for Multi-person Pose Estimation
inferredcites →https://doi.org/10.1109/cvpr.2018.00907openalex-snapshot
Learning Transferable Architectures for Scalable Image Recognition
inferredcites →https://doi.org/10.1109/cvpr.2018.00913openalex-snapshot
Path Aggregation Network for Instance Segmentation
inferredcites →https://doi.org/10.1109/cvpr.2019.00075openalex-snapshot
Generalized Intersection Over Union: A Metric and a Loss for Bounding Box Regression
inferredcites →https://doi.org/10.1109/cvpr.2019.00091openalex-snapshot
Libra R-CNN: Towards Balanced Learning for Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2019.00093openalex-snapshot
Feature Selective Anchor-Free Module for Single-Shot Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2019.00094openalex-snapshot
Bottom-Up Object Detection by Grouping Extreme and Center Points
inferredcites →https://doi.org/10.1109/cvpr.2019.00237openalex-snapshot
ScratchDet: Training Single-Shot Object Detectors From Scratch
inferredcites →https://doi.org/10.1109/cvpr.2019.00308openalex-snapshot
Region Proposal by Guided Anchoring
inferredcites →https://doi.org/10.1109/cvpr.2019.00511openalex-snapshot
Hybrid Task Cascade for Instance Segmentation
inferredcites →https://doi.org/10.1109/cvpr.2019.00526openalex-snapshot
Towards Accurate One-Stage Object Detection With AP-Loss
inferredcites →https://doi.org/10.1109/cvpr.2019.00533openalex-snapshot
High-Level Semantic Feature Detection: A New Perspective for Pedestrian Detection
inferredcites →https://doi.org/10.1109/cvpr.2019.00712openalex-snapshot
Strong-Weak Distribution Alignment for Adaptive Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2019.00720openalex-snapshot
NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2019.00751openalex-snapshot
Efficient Featurized Image Pyramid Network for Single Shot Detector
inferredcites →https://doi.org/10.1109/cvpr.2019.00757openalex-snapshot
Triply Supervised Decoder Networks for Joint Detection and Segmentation
inferredcites →https://doi.org/10.1109/cvpr.2019.00953openalex-snapshot
Deformable ConvNets V2: More Deformable, Better Results
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00978openalex-snapshot
Bridging the Gap Between Anchor-Based and Anchor-Free Detection via Adaptive Training Sample Selection
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01053openalex-snapshot
CentripetalNet: Pursuing High-Quality Keypoint Pairs for Object Detection
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01079openalex-snapshot
EfficientDet: Scalable and Efficient Object Detection
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01142openalex-snapshot
Hit-Detector: Hierarchical Trinity Architecture Search for Object Detection
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01158openalex-snapshot
Revisiting the Sibling Head in Object Detector
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01161openalex-snapshot
SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01196openalex-snapshot
NAS-FCOS: Fast Neural Architecture Search for Object Detection
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01218openalex-snapshot
DR Loss: Improving Object Detection by Distributional Ranking
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01261openalex-snapshot
AugFPN: Improving Multi-Scale Feature Learning for Object Detection
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01392openalex-snapshot
CenterMask: Real-Time Anchor-Free Instance Segmentation
inferredcites →https://doi.org/10.1109/cvpr46437.2021.00037openalex-snapshot
OTA: Optimal Transport Assignment for Object Detection
inferredcites →https://doi.org/10.1109/cvpr46437.2021.00165openalex-snapshot
UP-DETR: Unsupervised Pre-training for Object Detection with Transformers
inferredcites →https://doi.org/10.1109/cvpr46437.2021.00294openalex-snapshot
Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation
inferredcites →https://doi.org/10.1109/cvpr46437.2021.00382openalex-snapshot
MobileDets: Searching for Object Detection Architectures for Mobile Accelerators
inferredcites →https://doi.org/10.1109/cvpr46437.2021.00841openalex-snapshot
VarifocalNet: An IoU-aware Dense Object Detector
inferredcites →https://doi.org/10.1109/cvpr46437.2021.01008openalex-snapshot
DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution
inferredcites →https://doi.org/10.1109/cvpr46437.2021.01146openalex-snapshot
Generalized Focal Loss V2: Learning Reliable Localization Quality Estimation for Dense Object Detection
inferredcites →https://doi.org/10.1109/cvpr46437.2021.01215openalex-snapshot
Cross-Iteration Batch Normalization
inferredcites →https://doi.org/10.1109/cvpr46437.2021.01283openalex-snapshot
Scaled-YOLOv4: Scaling Cross Stage Partial Network
inferredcites →https://doi.org/10.1109/cvpr46437.2021.01284openalex-snapshot
You Only Look One-level Feature
inferredcites →https://doi.org/10.1109/cvpr46437.2021.01352openalex-snapshot
RepVGG: Making VGG-style ConvNets Great Again
inferredcites →https://doi.org/10.1109/cvpr46437.2021.01416openalex-snapshot
Open-Vocabulary Object Detection Using Captions
inferredcites →https://doi.org/10.1109/cvpr46437.2021.01422openalex-snapshot
Sparse R-CNN: End-to-End Object Detection with Learnable Proposals
inferredcites →https://doi.org/10.1109/cvpr46437.2021.01509openalex-snapshot
A2-FPN: Attention Aggregation based Feature Pyramid Network for Instance Segmentation
inferredcites →https://doi.org/10.1109/cvpr52688.2022.00476openalex-snapshot
MViTv2: Improved Multiscale Vision Transformers for Classification and Detection
inferredcites →https://doi.org/10.1109/cvpr52688.2022.00519openalex-snapshot
Recurrent Glimpse-based Decoder for Detection with Transformer
inferredcites →https://doi.org/10.1109/cvpr52688.2022.00529openalex-snapshot
AdaMixer: A Fast-Converging Query-Based Object Detector
inferredcites →https://doi.org/10.1109/cvpr52688.2022.01069openalex-snapshot
Grounded Language-Image Pre-training
inferredcites →https://doi.org/10.1109/cvpr52688.2022.01170openalex-snapshot
Swin Transformer V2: Scaling Up Capacity and Resolution
inferredcites →https://doi.org/10.1109/cvpr52688.2022.01325openalex-snapshot
DN-DETR: Accelerate DETR Training by Introducing Query DeNoising
inferredcites →https://doi.org/10.1109/cvpr52688.2022.01393openalex-snapshot
H2FA R-CNN: Holistic and Hierarchical Feature Alignment for Cross-domain Weakly Supervised Object Detection
inferredcites →https://doi.org/10.1109/cvpr52688.2022.01553openalex-snapshot
Masked Autoencoders Are Scalable Vision Learners
inferredcites →https://doi.org/10.1109/cvpr52729.2023.00608openalex-snapshot
DynamicDet: A Unified Dynamic Architecture for Object Detection
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CORA: Adapting CLIP for Open-Vocabulary Detection with Region Prompting and Anchor Pre-Matching
inferredcites →https://doi.org/10.1109/cvpr52729.2023.00721openalex-snapshot
YOLOv7: Trainable Bag-of-Freebies Sets New State-of-the-Art for Real-Time Object Detectors
inferredcites →https://doi.org/10.1109/cvpr52733.2024.00461openalex-snapshot
Florence-2: Advancing a Unified Representation for a Variety of Vision Tasks
inferredcites →https://doi.org/10.1109/cvpr52733.2024.01605openalex-snapshot
DETRs Beat YOLOs on Real-time Object Detection
inferredcites →https://doi.org/10.1109/cvprw.2009.5206631openalex-snapshot
Pedestrian detection: A benchmark
inferredcites →https://doi.org/10.1109/cvprw50498.2020.00203openalex-snapshot
CSPNet: A New Backbone that can Enhance Learning Capability of CNN
inferredcites →https://doi.org/10.1109/iccv.1999.790410openalex-snapshot
Object recognition from local scale-invariant features
inferredcites →https://doi.org/10.1109/iccv.2003.1238422openalex-snapshot
Detecting pedestrians using patterns of motion and appearance
inferredcites →https://doi.org/10.1109/iccv.2003.1238663openalex-snapshot
Video Google: a text retrieval approach to object matching in videos
inferredcites →https://doi.org/10.1109/iccv.2005.239openalex-snapshot
The pyramid match kernel: discriminative classification with sets of image features
inferredcites →https://doi.org/10.1109/iccv.2009.5459183openalex-snapshot
Multiple kernels for object detection
inferredcites →https://doi.org/10.1109/iccv.2009.5459207openalex-snapshot
An HOG-LBP human detector with partial occlusion handling
inferredcites →https://doi.org/10.1109/iccv.2011.6126229openalex-snapshot
Ensemble of exemplar-SVMs for object detection and beyond
inferredcites →https://doi.org/10.1109/iccv.2011.6126456openalex-snapshot
Segmentation as selective search for object recognition
inferredcites →https://doi.org/10.1109/iccv.2013.10openalex-snapshot
Regionlets for Generic Object Detection
inferredcites →https://doi.org/10.1109/iccv.2013.369openalex-snapshot
Segmentation Driven Object Detection with Fisher Vectors
inferredcites →https://doi.org/10.1109/iccv.2015.135openalex-snapshot
Object Detection via a Multi-region and Semantic Segmentation-Aware CNN Model
inferredcites →https://doi.org/10.1109/iccv.2015.178openalex-snapshot
Learning Deconvolution Network for Semantic Segmentation
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What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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