3 citations · 5 across the 20 of their papers we have counts for
24 papers
TACD: Distilling Efficient Text-to-Motion Models via Terminal Amplification Control
Wei-Jin Huang, Yuan-Ming Li, Kun-Yu Lin +8
Recent text-to-motion models have improved motion quality and instruction following, yet many-step denoising and large model components make deployment slow and memory-intensive. W…
Breaking : Cooperative Policy Optimization Improves Diverse LLM Reasoning
Haoxuan Chen, Tianming Liang, Wei-Shi Zheng +1
Reinforcement learning with verifiers (RLVR) has become a central paradigm for improving LLM reasoning, yet popular group-based optimization algorithms like GRPO often suffer from…
HarmoGS: Robust 3D Gaussian Splatting in the Wild via Conflict-Aware Gradient Harmonization
Yulei Kang, Tianze Zhu, Jian-Fang Hu +2
In-the-wild 3D Gaussian Splatting remains challenging due to transient distractors and illumination-induced cross-view appearance inconsistencies. Existing methods mainly rely on i…
Learning Action Manifold with Multi-view Latent Priors for Robotic Manipulation
Junjin Xiao, Dongyang Li, Yandan Yang +9
This paper tackles spatial perception and manipulation challenges in Vision-Language-Action (VLA) models. To address depth ambiguity from monocular input, we leverage a pre-trained…
Risk-Aware World Model Predictive Control for Generalizable End-to-End Autonomous Driving
Jiangxin Sun, Feng Xue, Teng Long +4
With advances in imitation learning (IL) and large-scale driving datasets, end-to-end autonomous driving (E2E-AD) has made great progress recently. Currently, IL-based methods have…
Refer-Agent: A Collaborative Multi-Agent System with Reasoning and Reflection for Referring Video Object Segmentation
Haichao Jiang, Tianming Liang, Wei-Shi Zheng +1
Referring Video Object Segmentation (RVOS) aims to segment objects in videos based on textual queries. Current methods mainly rely on large-scale supervised fine-tuning (SFT) of Mu…
Seg-ReSearch: Segmentation with Interleaved Reasoning and External Search
Tianming Liang, Qirui Du, Jian-Fang Hu +3
Segmentation based on language has been a popular topic in computer vision. While recent advances in multimodal large language models (MLLMs) have endowed segmentation systems with…
IRG-MotionLLM: Interleaving Motion Generation, Assessment and Refinement for Text-to-Motion Generation
Yuan-Ming Li, Qize Yang, Nan Lei +5
Recent advances in motion-aware large language models have shown remarkable promise for jointly learning motion understanding and generation knowledge. However, these models typica…
Image-to-Video Transfer Learning based on Image-Language Foundation Models: A Comprehensive Survey
Jinxuan Li, Chaolei Tan, Haoxuan Chen +4
Image-Language Foundation Models (ILFMs) have demonstrated remarkable success in vision-language understanding, providing transferable multimodal representations that generalize ac…
CoopDiff: Anticipating 3D Human-object Interactions via Contact-consistent Decoupled Diffusion
Xiaotong Lin, Tianming Liang, Jian-Fang Hu +5
3D human-object interaction (HOI) anticipation aims to predict the future motion of humans and their manipulated objects, conditioned on the historical context. Generally, the arti…
Temporal Continual Learning with Prior Compensation for Human Motion Prediction
Jianwei Tang, Jiangxin Sun, Xiaotong Lin +3
Human Motion Prediction (HMP) aims to predict future poses at different moments according to past motion sequences. Previous approaches have treated the prediction of various momen…
Long-RVOS: A Comprehensive Benchmark for Long-term Referring Video Object Segmentation
Tianming Liang, Haichao Jiang, Yuting Yang +4
Referring video object segmentation (RVOS) aims to identify, track and segment the objects in a video based on language descriptions, which has received great attention in recent y…
PVUW 2025 Challenge Report: Advances in Pixel-level Understanding of Complex Videos in the Wild
Henghui Ding, Chang Liu, Nikhila Ravi +33
This report provides a comprehensive overview of the 4th Pixel-level Video Understanding in the Wild (PVUW) Challenge, held in conjunction with CVPR 2025. It summarizes the challen…
Modeling Multiple Normal Action Representations for Error Detection in Procedural Tasks
Wei-Jin Huang, Yuan-Ming Li, Zhi-Wei Xia +4
Error detection in procedural activities is essential for consistent and correct outcomes in AR-assisted and robotic systems. Existing methods often focus on temporal ordering erro…
Panorama Generation From NFoV Image Done Right
Dian Zheng, Cheng Zhang, Xiao-Ming Wu +4
Generating 360-degree panoramas from narrow field of view (NFoV) image is a promising computer vision task for Virtual Reality (VR) applications. Existing methods mostly assess the…
ViSpeak: Visual Instruction Feedback in Streaming Videos
Shenghao Fu, Qize Yang, Yuan-Ming Li +6
Recent advances in Large Multi-modal Models (LMMs) are primarily focused on offline video understanding. Instead, streaming video understanding poses great challenges to recent mod…
ReferDINO-Plus: 2nd Solution for 4th PVUW MeViS Challenge at CVPR 2025
Tianming Liang, Haichao Jiang, Wei-Shi Zheng +1
Referring Video Object Segmentation (RVOS) aims to segment target objects throughout a video based on a text description. This task has attracted increasing attention in the field…
LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models
Shenghao Fu, Qize Yang, Qijie Mo +5
Recent open-vocabulary detectors achieve promising performance with abundant region-level annotated data. In this work, we show that an open-vocabulary detector co-training with a…
ReferDINO: Referring Video Object Segmentation with Visual Grounding Foundations
Tianming Liang, Kun-Yu Lin, Chaolei Tan +3
Referring video object segmentation (RVOS) aims to segment target objects throughout a video based on a text description. This is challenging as it involves deep vision-language un…
TechCoach: Towards Technical-Point-Aware Descriptive Action Coaching
Yuan-Ming Li, An-Lan Wang, Kun-Yu Lin +4
To guide a learner in mastering action skills, it is crucial for a coach to 1) reason through the learner's action execution and technical points (TechPoints), and 2) provide detai…
SynopGround: A Large-Scale Dataset for Multi-Paragraph Video Grounding from TV Dramas and Synopses
Chaolei Tan, Zihang Lin, Junfu Pu +7
Video grounding is a fundamental problem in multimodal content understanding, aiming to localize specific natural language queries in an untrimmed video. However, current video gro…
Ranking Distillation for Open-Ended Video Question Answering with Insufficient Labels
Tianming Liang, Chaolei Tan, Beihao Xia +2
This paper focuses on open-ended video question answering, which aims to find the correct answers from a large answer set in response to a video-related question. This is essential…
Selective Hourglass Mapping for Universal Image Restoration Based on Diffusion Model
Dian Zheng, Xiao-Ming Wu, Shuzhou Yang +3
Universal image restoration is a practical and potential computer vision task for real-world applications. The main challenge of this task is handling the different degradation dis…
Siamese Learning with Joint Alignment and Regression for Weakly-Supervised Video Paragraph Grounding
Chaolei Tan, Jianhuang Lai, Wei-Shi Zheng +1
Video Paragraph Grounding (VPG) is an emerging task in video-language understanding, which aims at localizing multiple sentences with semantic relations and temporal order from an…