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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:GitHub - mlpc-ucsd/TokenCompose: (arXiv) 🧩 TokenCompose: Grounding Diffusion with Token-level Supervision 

12.【多模态】FERGI: Automatic Annotation of User Preferences for Text-to-Image Generation from Spontaneous Facial Expression Reaction
-  论文地址:https://arxiv.org//pdf/2312.03187 
-  开源代码:GitHub - ShuangquanFeng/FERGI 

13.【多模态】Uni3DL: Unified Model for 3D and Language Understanding
-  论文地址:https://arxiv.org//pdf/2312.03026 
-  工程主页:Uni3DL 
-  开源代码(即将开源):https://github.com/lx709/Uni3DL 

14.【数字人】Gaussian Head Avatar: Ultra High-fidelity Head Avatar via Dynamic Gaussians
-  论文地址:https://arxiv.org//pdf/2312.03029 
-  工程主页:Gaussian Head Avatar's Project Page 
-  开源代码(即将开源):GitHub - YuelangX/Gaussian-Head-Avatar: Official repository for "Gaussian Head Avatar: Ultra High-fidelity Head Avatar via Dynamic Gaussians" 

15.【自动驾驶】Reason2Drive: Towards Interpretable and Chain-based Reasoning for Autonomous Driving
-  论文地址:https://arxiv.org//pdf/2312.03661 
-  开源代码(即将开源):GitHub - fudan-zvg/Reason2Drive: Reason2Drive: Towards Interpretable and Chain-based Reasoning for Autonomous Driving 

16.【自动驾驶】Open-sourced Data Ecosystem in Autonomous Driving: the Present and Future
-  论文地址:https://arxiv.org//pdf/2312.03408 
-  开源代码(即将开源):GitHub - OpenDriveLab/DriveAGI: Embracing Foundation Models into Autonomous Agent and System 

17.【自动驾驶】Online Vectorized HD Map Construction using Geometry
-  论文地址:https://arxiv.org//pdf/2312.03341 
-  工程主页:Online Vectorized HD Map Construction using Geometry 
-  开源代码:GitHub - cnzzx/GeMap: Online Vectorized HD Map Construction using Geometry 

18.【自动驾驶】Is Ego Status All You Need for Open-Loop End-to-End Autonomous Driving?
-  论文地址:https://arxiv.org//pdf/2312.03031 
-  开源代码(即将开源):GitHub - NVlabs/BEV-Planner 

19.【视频编辑】MagicStick: Controllable Video Editing via Control Handle Transformations
-  论文地址:https://arxiv.org//pdf/2312.03047 
-  工程主页:MagicStick🪄 
-  开源代码(即将开源):GitHub - mayuelala/MagicStick: MagicStick: This repo is the official implementation of "MagicStick: Controllable Video Editing via Control Handle Transformations" 

20.【人体运动生成】MMM: Generative Masked Motion Model
-  论文地址:https://arxiv.org//pdf/2312.03596 
-  工程主页:MMM: Generative Masked Motion Model 
-  开源代码(即将开源):GitHub - exitudio/MMM 

21.【姿态估计】FocalPose++: Focal Length and Object Pose Estimation via Render and Compare
-  论文地址:https://arxiv.org//pdf/2312.02985 
-  开源代码:GitHub - cifkam/FocalPosePP 

22.【NeRF】SO-NeRF: Active View Planning for NeRF using Surrogate Objectives
-  论文地址:https://arxiv.org//pdf/2312.03266 
-  工程主页:SO-NeRF 
-  开源代码(即将开源):https://github.com/ai4ce/SO-NeRF 

23.【图像合成】Self-conditioned Image Generation via Generating Representations
-  论文地址:https://arxiv.org//pdf/2312.03701 
-  开源代码:GitHub - LTH14/rcg: PyTorch implementation of RCG https://arxiv.org/abs/2312.03701 

24.【图像合成】LooseControl: Lifting ControlNet for Generalized Depth Conditioning
-  论文地址:https://arxiv.org//pdf/2312.03079 
-  工程主页:LooseControl 
-  开源代码:GitHub - shariqfarooq123/LooseControl: Lifting ControlNet for Generalized Depth Conditioning 

25.【视频生成】MotionCtrl: A Unified and Flexible Motion Controller for Video Generation
-  论文地址:https://arxiv.org//pdf/2312.03641 
-  工程主页:MotionCtrl 
-  开源代码(即将开源):GitHub - TencentARC/MotionCtrl 

26.【视频生成】DreamVideo: High-Fidelity Image-to-Video Generation with Image Retention and Text Guidance
-  论文地址:https://arxiv.org//pdf/2312.03018 
-  工程主页:DreamVideo: High-Fidelity Image-to-Video Generation with Image Retention and Text Guidance 
-  开源代码(即将开源):GitHub - anonymous0769/DreamVideo 

27.【三维重建】DreamComposer: Controllable 3D Object Generation via Multi-View Conditions
-  论文地址:https://arxiv.org//pdf/2312.03611 
-  工程主页:DreamComposer: Controllable 3D Object Generation via Multi-View Conditions 
-  开源代码(即将开源):GitHub - yhyang-myron/DreamComposer: [Arxiv23] DreamComposer: Controllable 3D Object Generation via Multi-View Conditions 

28.【数据蒸馏】On the Diversity and Realism of Distilled Dataset: An Efficient Dataset Distillation Paradigm
-  论文地址:https://arxiv.org//pdf/2312.03526 
-  开源代码(即将开源):https://github.com/LINs-lab/RDED 

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