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)…
Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision
Jie Hong, Tingtian Li, Xuesong Li +1
Depth estimation from thermal images is highly valuable for robotic applications in adverse conditions, such as nighttime and rainy weather. Recent studies have sought to transfer…
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…
EgoSelf: From Memory to Personalized Egocentric Assistant
Yanshuo Wang, Yuan Xu, Xuesong Li +4
Egocentric assistants often rely on first-person view data to capture user behavior and context for personalized services. Since different users exhibit distinct habits, preference…
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…
Latent-based Diffusion Model for Long-tailed Recognition
Pengxiao Han, Changkun Ye, Jieming Zhou +3
Long-tailed imbalance distribution is a common issue in practical computer vision applications. Previous works proposed methods to address this problem, which can be categorized in…