57 citations · 70 across the 14 of their papers we have counts for
16 papers
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…
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…
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…
Progressive Human Motion Generation Based on Text and Few Motion Frames
Ling-An Zeng, Gaojie Wu, Ancong Wu +2
Although existing text-to-motion (T2M) methods can produce realistic human motion from text description, it is still difficult to align the generated motion with the desired postur…
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…
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…
STVGFormer: Spatio-Temporal Video Grounding with Static-Dynamic Cross-Modal Understanding
Zihang Lin, Chaolei Tan, Jian-Fang Hu +3
In this technical report, we introduce our solution to human-centric spatio-temporal video grounding task. We propose a concise and effective framework named STVGFormer, which mode…
Weakly-Supervised Temporal Action Localization by Progressive Complementary Learning
Jia-Run Du, Jia-Chang Feng, Kun-Yu Lin +5
Weakly Supervised Temporal Action Localization (WSTAL) aims to localize and classify action instances in long untrimmed videos with only video-level category labels. Due to the lac…
Augmented 2D-TAN: A Two-stage Approach for Human-centric Spatio-Temporal Video Grounding
Chaolei Tan, Zihang Lin, Jian-Fang Hu +2
We propose an effective two-stage approach to tackle the problem of language-based Human-centric Spatio-Temporal Video Grounding (HC-STVG) task. In the first stage, we propose an A…
Improving Fast Segmentation With Teacher-student Learning
Jiafeng Xie, Bing Shuai, Jian-Fang Hu +2
Recently, segmentation neural networks have been significantly improved by demonstrating very promising accuracies on public benchmarks. However, these models are very heavy and ge…
Latent Embeddings for Collective Activity Recognition
Yongyi Tang, Peizhen Zhang, Jian-Fang Hu +1
Rather than simply recognizing the action of a person individually, collective activity recognition aims to find out what a group of people is acting in a collective scene. Previ-…