cs.CV(2025-11-05)

📊 共 10 篇论文 | 🔗 2 篇有代码

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支柱三:空间感知 (Perception & SLAM) (5 🔗2) 支柱二:RL算法与架构 (RL & Architecture) (1) 支柱五:交互与反应 (Interaction & Reaction) (1) 支柱六:视频提取与匹配 (Video Extraction & Matching) (1) 支柱四:生成式动作 (Generative Motion) (1) 支柱八:物理动画 (Physics-based Animation) (1)

🔬 支柱三:空间感知 (Perception & SLAM) (5 篇)

#题目一句话要点标签🔗
1 DentalSplat: Dental Occlusion Novel View Synthesis from Sparse Intra-Oral Photographs 提出DentalSplat以解决稀疏口腔影像下的牙齿咬合重建问题 3D gaussian splatting 3DGS gaussian splatting
2 SurgViVQA: Temporally-Grounded Video Question Answering for Surgical Scene Understanding SurgViVQA:面向手术场景理解的时序视频问答模型 scene understanding
3 IEC3D-AD: A 3D Dataset of Industrial Equipment Components for Unsupervised Point Cloud Anomaly Detection 提出IEC3D-AD工业零件3D异常检测数据集及GMANet异常检测方法 point cloud
4 Subsampled Randomized Fourier GaLore for Adapting Foundation Models in Depth-Driven Liver Landmark Segmentation 提出SRFT-GaLore,用于深度驱动的肝脏地标分割中高效自适应基础模型。 monocular depth localization Depth Anything
5 Beyond Softmax: Dual-Branch Sigmoid Architecture for Accurate Class Activation Maps 提出双分支Sigmoid架构,解决CAM中logit偏移和符号坍塌问题,提升定位精度。 localization

🔬 支柱二:RL算法与架构 (RL & Architecture) (1 篇)

#题目一句话要点标签🔗
6 Investigating Robot Control Policy Learning for Autonomous X-ray-guided Spine Procedures 提出基于模仿学习的机器人控制策略,用于X射线引导的脊柱手术 policy learning imitation learning navigation

🔬 支柱五:交互与反应 (Interaction & Reaction) (1 篇)

#题目一句话要点标签🔗
7 Part-Aware Bottom-Up Group Reasoning for Fine-Grained Social Interaction Detection 提出Part-Aware自底向上群体推理框架,用于细粒度社交互动检测 social interaction

🔬 支柱六:视频提取与匹配 (Video Extraction & Matching) (1 篇)

#题目一句话要点标签🔗
8 Human Mesh Modeling for Anny Body 提出Anny:一个基于人体测量学知识的可微、无扫描的人体网格建模方法 human mesh recovery HMR

🔬 支柱四:生成式动作 (Generative Motion) (1 篇)

#题目一句话要点标签🔗
9 UniAVGen: Unified Audio and Video Generation with Asymmetric Cross-Modal Interactions UniAVGen:提出一种非对称跨模态交互的统一音视频生成框架 classifier-free guidance

🔬 支柱八:物理动画 (Physics-based Animation) (1 篇)

#题目一句话要点标签🔗
10 Computed Tomography (CT)-derived Cardiovascular Flow Estimation Using Physics-Informed Neural Networks Improves with Sinogram-based Training: A Simulation Study 提出SinoFlow:利用Sinogram数据训练的物理信息神经网络提升CT血流估计精度 PULSE

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