12 papers
A Differentiable Optimization Framework for Registering Sequential Bounding Boxes with Point Cloud Stream
Xuesong Li, Jinguang Tong, Jie Hong
Refining a sequence of coarse 3D bounding boxes against a LiDAR point-cloud stream demands tracks that are geometrically accurate (high IoU) and temporally coherent (low roughness)…
Keep the Future, Drop the Rollout: RIFT for World Action Models
Chushan Zhang, Jinguang Tong, Xuesong Li +2
World action models (WAMs) condition robot actions on predicted futures, but iterative video rollout increases deployment latency. We ask whether action generation requires the evo…
Label Shift Aware Adaptation for Online Zero-shot Learning with Contrastive Language-Image Pre-Training (CLIP)
Pengxiao Han, Changkun Ye, Yanshuo Wang +5
Vision-language models like Contrastive Language-Image Pre-Training (CLIP) have been extensively studied in data-scarce scenarios. A particularly challenging and realistic task in…
Structural Energy Guidance for View-Consistent Text-to-3D Generation
Qing Zhang, Jinguang Tong, Jing Zhang +2
Text-to-3D generation based on diffusion models often suffers from the Janus problem, leading to inconsistent geometry across viewpoints. This work identifies viewpoint bias in 2D…
EvoScene-VLA: Evolving Scene Beliefs Inside the Action Decoder for Chunked Robot Control
Chushan Zhang, Ruihan Lu, Jinguang Tong +3
Chunked vision-language-action (VLA) policies generate multi-step actions from one observation and typically re-observe after executing the action chunk. Earlier actions change the…
MVHOI: Bridge Multi-view Condition to Complex Human-Object Interaction Video Reenactment via 3D Foundation Model
Jinguang Tong, Jinbo Wu, Kaisiyuan Wang +12
Human-Object Interaction (HOI) video reenactment aims to transfer the interaction dynamics of a source video to a novel target object while preserving realistic hand-object coordin…
Adaptive and Balanced Re-initialization for Long-timescale Continual Test-time Domain Adaptation
Yanshuo Wang, Jinguang Tong, Jun Lan +5
Continual test-time domain adaptation (CTTA) aims to adjust models so that they can perform well over time across non-stationary environments. While previous methods have made cons…
Structural Energy-Guided Sampling for View-Consistent Text-to-3D
Qing Zhang, Jinguang Tong, Jie Hong +2
Text-to-3D generation often suffers from the Janus problem, where objects look correct from the front but collapse into duplicated or distorted geometry from other angles. We attri…
Enhancing Features in Long-tailed Data Using Large Vision Model
Pengxiao Han, Changkun Ye, Jinguang Tong +4
Language-based foundation models, such as large language models (LLMs) or large vision-language models (LVLMs), have been widely studied in long-tailed recognition. However, the ne…
Maintain Plasticity in Long-timescale Continual Test-time Adaptation
Yanshuo Wang, Xuesong Li, Jinguang Tong +5
Continual test-time domain adaptation (CTTA) aims to adjust pre-trained source models to perform well over time across non-stationary target environments. While previous methods ha…
DGNS: Deformable Gaussian Splatting and Dynamic Neural Surface for Monocular Dynamic 3D Reconstruction
Xuesong Li, Jinguang Tong, Jie Hong +2
Dynamic scene reconstruction from monocular video is essential for real-world applications. We introduce DGNS, a hybrid framework integrating \underline{D}eformable \underline{G}au…
Improving Viewpoint Consistency in 3D Generation via Structure Feature and CLIP Guidance
Qing Zhang, Jinguang Tong, Jing Zhang +2
Despite recent advances in text-to-3D generation techniques, current methods often suffer from geometric inconsistencies, commonly referred to as the Janus Problem. This paper iden…