8 citations · 8 across the 14 of their papers we have counts for
15 papers
Human Motion Prediction via Continual Prior Compensation
Jianwei Tang, Jian-Fang Hu, Tianming Liang +4
Human Motion Prediction (HMP) aims to predict future human poses at different moments according to observed past motion sequences. Previous approaches mainly treated the prediction…
Don't Guess, Just Ask: Resolving Ambiguity in Referring Segmentation via Multi-turn Clarification
Yuting Yang, Haichao Jiang, Tianming Liang +2
Referring segmentation aims to segment the target objects in images or videos based on the textual query. Despite remarkable progress over the past years, existing works always ass…
Decoupling Endpoint and Semantic Transition Learning for Zero-Shot Composed Image Retrieval
Mingyu Liu, Sihan Huang, Yijia Fan +4
Zero-shot composed image retrieval (ZS-CIR) retrieves a target image from a reference image and a text modification without human-annotated CIR triplets. Projection-based ZS-CIR me…
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…
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…
TubeRMC: Tube-conditioned Reconstruction with Mutual Constraints for Weakly-supervised Spatio-Temporal Video Grounding
Jinxuan Li, Yi Zhang, Jian-Fang Hu +3
Spatio-Temporal Video Grounding (STVG) aims to localize a spatio-temporal tube that corresponds to a given language query in an untrimmed video. This is a challenging task since it…
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…
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…
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…
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…