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1.【显著目标检测】Texture-Semantic Collaboration Network for ORSI Salient Object Detection

• 论文地址：https://arxiv.org//pdf/2312.03548

• 开源代码：GitHub - MathLee/TSCNet: [TCAS-II 2023] [TSCNet] Texture-Semantic Collaboration Network for ORSI Salient Object Detection

2.【图像分割】Boosting Segment Anything Model Towards Open-Vocabulary Learning

• 论文地址：https://arxiv.org//pdf/2312.03628

• 开源代码（即将开源）：GitHub - ucas-vg/Sambor: Sambor: Boosting Segment Anything Model Towards Open-Vocabulary Learning

3.【图像分割】Improving the Generalization of Segmentation Foundation Model under Distribution Shift via Weakly Supervised Adaptation

• 论文地址：https://arxiv.org//pdf/2312.03502

• 开源代码（即将开源）：GitHub - zhang-haojie/wesam

4.【语义分割】ShareCMP: Polarization-Aware RGB-P Semantic Segmentation

• 论文地址：https://arxiv.org//pdf/2312.03430

• 开源代码（即将开源）：GitHub - LEFTeyex/ShareCMP: ShareCMP: Polarization-Aware RGB-P Semantic Segmentation.

5.【语义分割】DGInStyle: Domain-Generalizable Semantic Segmentation with Image Diffusion Models and Stylized Semantic Control

• 论文地址：https://arxiv.org//pdf/2312.03048

• 工程主页：DGInStyle: Domain-Generalizable Semantic Segmentation with Image Diffusion Models and Stylized Semantic Control

• 代码即将开源

6.【点云分割】PartSLIP++: Enhancing Low-Shot 3D Part Segmentation via Multi-View Instance Segmentation and Maximum Likelihood Estimation

• 论文地址：https://arxiv.org//pdf/2312.03015

• 开源代码：GitHub - zyc00/PartSLIP2

7.【医学图像分割】AI-SAM: Automatic and Interactive Segment Anything Model

• 论文地址：https://arxiv.org//pdf/2312.03119

• 开源代码（即将开源）：GitHub - ymp5078/AI-SAM: AI-SAM: Automatic and Interactive Segment Anything Model

8.【动作识别】STEP CATFormer: Spatial-Temporal Effective Body-Part Cross Attention Transformer for Skeleton-based Action Recognition

• 论文地址：https://arxiv.org//pdf/2312.03288

• 开源代码（即将开源）：GitHub - maclong01/STEP-CATFormer: [BMVC 2023] Official code for "STEP CATFormer: Spatial-Temporal Effective Body-Part Cross Attention Transformer for Skeleton-based Action Recognition"

9.【多模态】OneLLM: One Framework to Align All Modalities with Language

• 论文地址：https://arxiv.org//pdf/2312.03700

• 开源代码：GitHub - csuhan/OneLLM: OneLLM: One Framework to Align All Modalities with Language

10.【多模态】MOCHa: Multi-Objective Reinforcement Mitigating Caption Hallucinations

• 论文地址：https://arxiv.org//pdf/2312.03631

• 工程主页：MOCHa: Multi-Objective Reinforcement Mitigating Caption Hallucinations

• 开源代码（即将开源）：GitHub - assafbk/mocha_code: Code Repo for MOCHa: Multi-Objective Reinforcement Mitigating Caption Hallucinations

11.【多模态】TokenCompose: Grounding Diffusion with Token-level Supervision

• 论文地址：https://arxiv.org//pdf/2312.03626

• 工程主页：TokenCompose: Grounding Diffusion with Token-level Supervision

• 开源代码：https://www.wpsshop.cn/article/detail/59549