2 citations · 2 across the 12 of their papers we have counts for
13 papers · 1 filter
WeVisOne-VL: Unified Visual Perception from Objects to Pixels
Tianming Liang, Junyi Pan, Yuxi Li +5
Existing vision-language models (VLMs) remain unreliable for fine-grained visual perception. In this report, we present WeVisOne-VL (WeChat Vision All-in-One), a powerful VLM that…
Kwai Keye-VL-2.0 Technical Report
Kwai Keye Team, Bin Wen, Changyi Liu +50
We introduce Kwai Keye-VL-2.0-30B-A3B, an open-source Mixture-of-Experts (MoE) multimodal foundation model designed to advance long-video understanding and agentic intelligence. To…
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…
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…
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…
Progressive Pretext Task Learning for Human Trajectory Prediction
Xiaotong Lin, Tianming Liang, Jianhuang Lai +1
Human trajectory prediction is a practical task of predicting the future positions of pedestrians on the road, which typically covers all temporal ranges from short-term to long-te…
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…