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cs.CV2026

DailyArt: Discovering Articulation from Single Static Images via Latent Dynamics

Hang Zhang, Qijian Tian, Jingyu Gong +4

Articulated objects are essential for embodied AI and world models, yet inferring their kinematics from a single closed-state image remains challenging because crucial motion cues…

cs.CV2026

FlashMotion: Few-Step Controllable Video Generation with Trajectory Guidance

Quanhao Li, Zhen Xing, Rui Wang +4

Recent advances in trajectory-controllable video generation have achieved remarkable progress. Previous methods mainly use adapter-based architectures for precise motion control al…

cs.CV2026

Preference Score Distillation: Leveraging 2D Rewards to Align Text-to-3D Generation with Human Preference

Jiaqi Leng, Shuyuan Tu, Haidong Cao +4

Human preference alignment presents a critical yet underexplored challenge for diffusion models in text-to-3D generation. Existing solutions typically require task-specific fine-tu…

cs.CV2026

UniHand: A Unified Model for Diverse Controlled 4D Hand Motion Modeling

Zhihao Sun, Tong Wu, Ruirui Tu +2

Hand motion plays a central role in human interaction, yet modeling realistic 4D hand motion (i.e., 3D hand pose sequences over time) remains challenging. Research in this area is…

cs.CV2025

DeRA: Decoupled Representation Alignment for Video Tokenization

Pengbo Guo, Junke Wang, Zhen Xing +4

This paper presents DeRA, a novel 1D video tokenizer that decouples the spatial-temporal representation learning in video tokenization to achieve better training efficiency and per…

cs.CV2025

Preserving Cross-Modal Consistency for CLIP-based Class-Incremental Learning

Haoran Chen, Houze Xu, Micah Goldblum +2

Class-incremental learning (CIL) enables models to continuously learn new categories from sequential tasks without forgetting previously acquired knowledge. While recent advances i…