activity
20232026
most citedTMT-VIS: Taxonomy-aware Multi-dataset Joint Training for Video Instance Segmentation

1 citations · 1 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV2026

SpatialUAV: Benchmarking Spatial Intelligence for Low-Altitude UAV Perception, Collaboration, and Motion

Haoyu Zhang, Meng Liu, Qianlong Xiang +3

Spatial intelligence is essential for low-altitude unmanned aerial vehicle (UAV) perception, collaboration, and navigation. However, existing UAV benchmarks often emphasize image-l…

cs.LG2026

SaFeR-ToolKit: Structured Reasoning via Virtual Tool Calling for Multimodal Safety

Zixuan Xu, Tiancheng He, Huahui Yi +7

Vision-language models remain susceptible to multimodal jailbreaks and over-refusal because safety hinges on both visual evidence and user intent, while many alignment pipelines su…

cs.CV2025

Seg-VAR: Image Segmentation with Visual Autoregressive Modeling

Rongkun Zheng, Lu Qi, Xi Chen +3

While visual autoregressive modeling (VAR) strategies have shed light on image generation with the autoregressive models, their potential for segmentation, a task that requires pre…

cs.CV2024

SyncVIS: Synchronized Video Instance Segmentation

Rongkun Zheng, Lu Qi, Xi Chen +4

Recent DETR-based methods have advanced the development of Video Instance Segmentation (VIS) through transformers' efficiency and capability in modeling spatial and temporal inform…

cs.CV2024

ViLLa: Video Reasoning Segmentation with Large Language Model

Rongkun Zheng, Lu Qi, Xi Chen +4

Recent efforts in video reasoning segmentation (VRS) integrate large language models (LLMs) with perception models to localize and track objects via textual instructions, achieving…

cs.CV2023★ 1 cited

TMT-VIS: Taxonomy-aware Multi-dataset Joint Training for Video Instance Segmentation

Rongkun Zheng, Lu Qi, Xi Chen +4

Training on large-scale datasets can boost the performance of video instance segmentation while the annotated datasets for VIS are hard to scale up due to the high labor cost. What…