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Drkd: Rethinking and Decoupling Response Distillation for Object Detection

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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-030-01234-2_1openalex-snapshot

CBAM: Convolutional Block Attention Module

inferredcites →https://doi.org/10.1007/978-3-030-58452-8_13openalex-snapshot

End-to-End Object Detection with Transformers

inferredcites →https://doi.org/10.1007/978-3-031-20077-9_25openalex-snapshot

Distilling Object Detectors with Global Knowledge

inferredcites →https://doi.org/10.1007/978-3-031-20077-9_8openalex-snapshot

Prediction-Guided Distillation for Dense Object Detection

inferredcites →https://doi.org/10.1007/978-3-319-46448-0_2openalex-snapshot

SSD: Single Shot MultiBox Detector

inferredcites →https://doi.org/10.1007/s11263-019-01204-1openalex-snapshot

CornerNet: Detecting Objects as Paired Keypoints

inferredcites →https://doi.org/10.1016/j.patcog.2023.109320openalex-snapshot

Task-balanced distillation for object detection

inferredcites →https://doi.org/10.1109/cvpr.2016.521openalex-snapshot

Quantized Convolutional Neural Networks for Mobile Devices

inferredcites →https://doi.org/10.1109/cvpr.2017.754openalex-snapshot

A Gift from Knowledge Distillation: Fast Optimization, Network Minimization and Transfer Learning

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.2019.00292openalex-snapshot

Fully Quantized Network for Object Detection

inferredcites →https://doi.org/10.1109/cvpr.2019.00507openalex-snapshot

Distilling Object Detectors With Fine-Grained Feature Imitation

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/cvpr46437.2021.00219openalex-snapshot

Distilling Object Detectors via Decoupled Features

inferredcites →https://doi.org/10.1109/cvpr46437.2021.00775openalex-snapshot

General Instance Distillation for Object Detection

inferredcites →https://doi.org/10.1109/cvpr52688.2022.00460openalex-snapshot

Focal and Global Knowledge Distillation for Detectors

inferredcites →https://doi.org/10.1109/cvpr52733.2024.01563openalex-snapshot

CrossKD: Cross-Head Knowledge Distillation for Object Detection

inferredcites →https://doi.org/10.1109/cvprw.2009.5206848openalex-snapshot

ImageNet: A large-scale hierarchical image database

inferredcites →https://doi.org/10.1109/iccv.2019.00667openalex-snapshot

CenterNet: Keypoint Triplets for Object Detection

inferredcites →https://doi.org/10.1109/iccv.2019.00972openalex-snapshot

FCOS: Fully Convolutional One-Stage Object Detection

inferredcites →https://doi.org/10.1109/iccv48922.2021.00349openalex-snapshot

TOOD: Task-aligned One-stage Object Detection

inferredcites →https://doi.org/10.1109/iccv48922.2021.00357openalex-snapshot

G-DetKD: Towards General Distillation Framework for Object Detectors via Contrastive and Semantic-guided Feature Imitation

inferredcites →https://doi.org/10.1109/iccv48922.2021.00432openalex-snapshot

Deep Structured Instance Graph for Distilling Object Detectors

inferredcites →https://doi.org/10.1109/iccv51070.2023.00577openalex-snapshot

Anchor-Intermediate Detector: Decoupling and Coupling Bounding Boxes for Accurate Object Detection

inferredcites →https://doi.org/10.1109/iccv51070.2023.01575openalex-snapshot

Bridging Cross-task Protocol Inconsistency for Distillation in Dense Object Detection

inferredcites →https://doi.org/10.1109/tpami.2016.2577031openalex-snapshot

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

inferredcites →https://doi.org/10.1109/tpami.2018.2858826openalex-snapshot

Focal Loss for Dense Object Detection

inferredcites →https://doi.org/10.1109/tpami.2023.3248583openalex-snapshot

Localization Distillation for Object Detection

inferredcites →https://doi.org/10.1145/2964284.2967274openalex-snapshot

UnitBox

inferredcites →https://doi.org/10.1145/3474085.3475351openalex-snapshot

Disentangle Your Dense Object Detector

inferredcites →https://doi.org/10.1609/aaai.v36i2.20018openalex-snapshot

Knowledge Distillation for Object Detection via Rank Mimicking and Prediction-Guided Feature Imitation

inferredcites →https://doi.org/10.4230/lipics.itp.2023.19openalex-snapshot

Exploiting Generative AI to Scale up Intelligent Tutoring Systems

inferredcites →https://doi.org/10.48550/arxiv.1412.6550openalex-snapshot

FitNets: Hints for Thin Deep Nets

inferredcites →https://doi.org/10.48550/arxiv.1503.02531openalex-snapshot

Distilling the Knowledge in a Neural Network

inferredcites →https://doi.org/10.48550/arxiv.1709.01507openalex-snapshot

Squeeze-and-Excitation Networks

inferredcites →https://doi.org/10.48550/arxiv.2006.04388openalex-snapshot

Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection

inferredcites →https://doi.org/10.48550/arxiv.2010.11929openalex-snapshot

An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

inferredcites →https://doi.org/10.48550/arxiv.2111.00674openalex-snapshot

Distilling Object Detectors with Feature Richness

inferredcites →https://doi.org/10.52202/068431-0279openalex-snapshot

Structural Knowledge Distillation for Object Detection

inferredcites →https://doi.org/10.52202/068431-1120openalex-snapshot

PKD: General Distillation Framework for Object Detectors Via Pearson Correlation Coefficient

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