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1.【显著目标检测】Texture-Semantic Collaboration Network for ORSI Salient Object Detection 论文地址#xff1a;https://arxiv.org//pdf/…点击计算机视觉关注更多CV干货
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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 Avatars 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 论文已打包下载链接
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