4 citations · 7 across the 7 of their papers we have counts for
8 papers
Are Image Generators Zero-Shot Perceivers? A Rigorous Evaluation
Shangzhe Di, Zhaokai Wang, Weidi Xie
Recent work, such as Vision Banana, shows that lightweight instruction tuning can enable an image generator to achieve state-of-the-art performance across multiple visual perceptio…
Towards Comprehensive Basketball Understanding
Yirong Hu, Jiayuan Rao, Yu Zhang +2
Understanding a basketball game requires recognizing events, localizing actions, identifying players, and relating these to structured game knowledge. Existing benchmarks primarily…
Weaver: End-to-End Agentic System Training for Video Interleaved Reasoning
Yudi Shi, Shangzhe Di, Qirui Chen +5
Video reasoning constitutes a comprehensive assessment of a model's capabilities, as it demands robust perceptual and interpretive skills, thereby serving as a means to explore the…
MTV: Revisiting Multi-Task Visual Representation Learning
Shangzhe Di, Zhonghua Zhai, Weidi Xie
Current visual representation learning remains bifurcated: vision-language models (e.g., CLIP) excel at global semantic alignment but lack spatial precision, while self-supervised…
Object-centric Video Question Answering with Visual Grounding and Referring
Haochen Wang, Qirui Chen, Cilin Yan +5
Video Large Language Models (VideoLLMs) have recently demonstrated remarkable progress in general video understanding. However, existing models primarily focus on high-level compre…
WorldSense: Evaluating Real-world Omnimodal Understanding for Multimodal LLMs
Jack Hong, Shilin Yan, Jiayin Cai +3
We introduce WorldSense, the first benchmark to assess the multi-modal video understanding, that simultaneously encompasses visual, audio, and text inputs. In contrast to existing…
VISA: Reasoning Video Object Segmentation via Large Language Models
Cilin Yan, Haochen Wang, Shilin Yan +5
Existing Video Object Segmentation (VOS) relies on explicit user instructions, such as categories, masks, or short phrases, restricting their ability to perform complex video segme…
A Sanity Check for AI-generated Image Detection
Shilin Yan, Ouxiang Li, Jiayin Cai +4
With the rapid development of generative models, discerning AI-generated content has evoked increasing attention from both industry and academia. In this paper, we conduct a sanity…