On the public citation graph

Dual‐branch mutual assistance network for salient object detection

0 signed · 48 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.

Claim with ORCID

Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.

See reference health

What this work says

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

inferredcites →https://doi.org/10.1007/978-3-030-01261-8_1openalex-snapshot

Group Normalization

inferredcites →https://doi.org/10.1007/978-3-030-58536-5_3openalex-snapshot

Suppress and Balance: A Simple Gated Network for Salient Object Detection

inferredcites →https://doi.org/10.1007/978-3-030-58539-6_42openalex-snapshot

Highly Efficient Salient Object Detection with 100K Parameters

inferredcites →https://doi.org/10.1016/j.patcog.2019.107130openalex-snapshot

Non-rigid object tracking via deep multi-scale spatial-temporal discriminative saliency maps

inferredcites →https://doi.org/10.1109/cvpr.2009.5206596openalex-snapshot

Frequency-tuned salient region detection

inferredcites →https://doi.org/10.1109/cvpr.2012.6247743openalex-snapshot

Saliency filters: Contrast based filtering for salient region detection

inferredcites →https://doi.org/10.1109/cvpr.2013.153openalex-snapshot

Hierarchical Saliency Detection

inferredcites →https://doi.org/10.1109/cvpr.2013.407openalex-snapshot

Saliency Detection via Graph-Based Manifold Ranking

inferredcites →https://doi.org/10.1109/cvpr.2014.360openalex-snapshot

Saliency Optimization from Robust Background Detection

inferredcites →https://doi.org/10.1109/cvpr.2014.39openalex-snapshot

How to Evaluate Foreground Maps

inferredcites →https://doi.org/10.1109/cvpr.2014.43openalex-snapshot

The Secrets of Salient Object Segmentation

inferredcites →https://doi.org/10.1109/cvpr.2015.7299184openalex-snapshot

Visual saliency based on multiscale deep features

inferredcites →https://doi.org/10.1109/cvpr.2016.395openalex-snapshot

Saliency Guided Dictionary Learning for Weakly-Supervised Image Parsing

inferredcites →https://doi.org/10.1109/cvpr.2016.58openalex-snapshot

Deep Contrast Learning for Salient Object Detection

inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot

Deep Residual Learning for Image Recognition

inferredcites →https://doi.org/10.1109/cvpr.2017.404openalex-snapshot

Learning to Detect Salient Objects with Image-Level Supervision

inferredcites →https://doi.org/10.1109/cvpr.2017.563openalex-snapshot

Deeply Supervised Salient Object Detection with Short Connections

inferredcites →https://doi.org/10.1109/cvpr.2017.698openalex-snapshot

Non-local Deep Features for Salient Object Detection

inferredcites →https://doi.org/10.1109/cvpr.2018.00081openalex-snapshot

Progressive Attention Guided Recurrent Network for Salient Object Detection

inferredcites →https://doi.org/10.1109/cvpr.2018.00187openalex-snapshot

A Bi-Directional Message Passing Model for Salient Object Detection

inferredcites →https://doi.org/10.1109/cvpr.2018.00326openalex-snapshot

PiCANet: Learning Pixel-Wise Contextual Attention for Saliency Detection

inferredcites →https://doi.org/10.1109/cvpr.2019.00065openalex-snapshot

Bag of Tricks for Image Classification with Convolutional Neural Networks

inferredcites →https://doi.org/10.1109/cvpr.2019.00154openalex-snapshot

Salient Object Detection With Pyramid Attention and Salient Edges

inferredcites →https://doi.org/10.1109/cvpr.2019.00172openalex-snapshot

Attentive Feedback Network for Boundary-Aware Salient Object Detection

inferredcites →https://doi.org/10.1109/cvpr.2019.00403openalex-snapshot

Cascaded Partial Decoder for Fast and Accurate Salient Object Detection

inferredcites →https://doi.org/10.1109/cvpr.2019.00404openalex-snapshot

A Simple Pooling-Based Design for Real-Time Salient Object Detection

inferredcites →https://doi.org/10.1109/cvpr.2019.00766openalex-snapshot

BASNet: Boundary-Aware Salient Object Detection

inferredcites →https://doi.org/10.1109/cvpr42600.2020.00916openalex-snapshot

Interactive Two-Stream Decoder for Accurate and Fast Saliency Detection

inferredcites →https://doi.org/10.1109/cvpr42600.2020.00943openalex-snapshot

Multi-Scale Interactive Network for Salient Object Detection

inferredcites →https://doi.org/10.1109/cvpr42600.2020.01304openalex-snapshot

Label Decoupling Framework for Salient Object Detection

inferredcites →https://doi.org/10.1109/iccv.2015.123openalex-snapshot

Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

inferredcites →https://doi.org/10.1109/iccv.2017.31openalex-snapshot

Amulet: Aggregating Multi-level Convolutional Features for Salient Object Detection

inferredcites →https://doi.org/10.1109/iccv.2019.00390openalex-snapshot

Selectivity or Invariance: Boundary-Aware Salient Object Detection

inferredcites →https://doi.org/10.1109/iccv.2019.00736openalex-snapshot

Stacked Cross Refinement Network for Edge-Aware Salient Object Detection

inferredcites →https://doi.org/10.1109/iccv.2019.00887openalex-snapshot

EGNet: Edge Guidance Network for Salient Object Detection

inferredcites →https://doi.org/10.1109/tpami.2014.2345401openalex-snapshot

Global Contrast Based Salient Region Detection

inferredcites →https://doi.org/10.1109/tpami.2019.2938758openalex-snapshot

Res2Net: A New Multi-Scale Backbone Architecture

inferredcites →https://doi.org/10.1609/aaai.v32i1.12298openalex-snapshot

Recurrently Aggregating Deep Features for Salient Object Detection

inferredcites →https://doi.org/10.1609/aaai.v34i07.6633openalex-snapshot

Global Context-Aware Progressive Aggregation Network for Salient Object Detection

inferredcites →https://doi.org/10.1609/aaai.v34i07.6916openalex-snapshot

F³Net: Fusion, Feedback and Focus for Salient Object Detection

inferredcites →https://doi.org/10.24963/ijcai.2018/95openalex-snapshot

R³Net: Recurrent Residual Refinement Network for Saliency Detection

inferredcites →https://doi.org/10.24963/ijcai.2018/97openalex-snapshot

Enhanced-alignment Measure for Binary Foreground Map Evaluation

inferredcites →https://doi.org/10.48550/arxiv.1210.5644openalex-snapshot

Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials

inferredcites →https://doi.org/10.48550/arxiv.1409.1556openalex-snapshot

Very Deep Convolutional Networks for Large-Scale Image Recognition

inferredcites →https://doi.org/10.48550/arxiv.1912.01703openalex-snapshot

PyTorch: An Imperative Style, High-Performance Deep Learning Library

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4876039openalex-extracted

Small Object Detection Network Based on Attention Mechanism and Feature Fusion

inferred← citeshttps://doi.org/10.1016/j.compbiomed.2022.106427openalex-snapshot

Transformer-based multilevel region and edge aggregation network for magnetic resonance image segmentation

inferred← citeshttps://doi.org/10.1155/2023/6266209openalex-snapshot

ALFPN: Adaptive Learning Feature Pyramid Network for Small Object Detection

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.