Bilateral Reference for High-Resolution Dichotomous Image Segmentation
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Cited by 20 in Diffusion models, but placed by its own abstract, which didn’t fit.
Abstract (arXiv)
We introduce a novel bilateral reference framework (BiRefNet) for high-resolution dichotomous image segmentation (DIS). It comprises two essential components: the localization module (LM) and the reconstruction module (RM) with our proposed bilateral reference (BiRef). The LM aids in object localization using global semantic information. Within the RM, we utilize BiRef for the reconstruction process, where hierarchical patches of images provide the source reference and gradient maps serve as the target reference. These components collaborate to generate the final predicted maps. We also introduce auxiliary gradient supervision to enhance focus on regions with finer details. Furthermore, we outline practical training strategies tailored for DIS to improve map quality and training process. To validate the general applicability of our approach, we conduct extensive experiments on four tasks to evince that BiRefNet exhibits remarkable performance, outperforming task-specific cutting-edge methods across all benchmarks. Our codes are available at https://github.com/ZhengPeng7/BiRefNet.
Key facts. Cited by 112 papers in the map (data through 7 Oct 2026). Builds on 46 of its 66 references that are in the map. First posted on arXiv 7 Jan 2024.
Builds on
46 of 66 references.
References · 46
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- 2021Anabranch Network for Camouflaged Object Segmentationcited by 227
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- 2022Zoom In and Out: A Mixed-scale Triplet Network for Camouflaged Object Detectioncited by 145
- 2017Fast and Accurate Image Super-Resolution with Deep Laplacian Pyramid Networkscited by 138
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- 2022A Deep Learning based No-reference Quality Assessment Model for UGC Videoscited by 128
- 2020Label Decoupling Framework for Salient Object Detectioncited by 111
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- 2019Towards High-Resolution Salient Object Detectioncited by 92
- 2020Bridging Composite and Real: Towards End-to-end Deep Image Mattingcited by 89
- 2023Feature Shrinkage Pyramid for Camouflaged Object Detection with Transformerscited by 87
- 2020Mask Guided Matting via Progressive Refinement Networkcited by 84
- 2022High-resolution Iterative Feedback Network for Camouflaged Object Detectioncited by 78
- 2021Blind Quality Assessment for in-the-Wild Images via Hierarchical Feature Fusion and Iterative Mixed Database Trainingcited by 71
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- 2022Deep Gradient Learning for Efficient Camouflaged Object Detectioncited by 65
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- 2021Look Closer to Segment Better: Boundary Patch Refinement for Instance Segmentationcited by 43
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- 2023Recurrent Multi-scale Transformer for High-Resolution Salient Object Detectioncited by 15
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