activity
20242026
collaborators

11 papers

cs.CV2026

OmniGen2: Towards Instruction-Aligned Multimodal Generation

Chenyuan Wu, Pengfei Zheng, Ruiran Yan +19

In this work, we introduce OmniGen2, a versatile and open-source generative model designed to provide a unified solution for diverse generation tasks, including text-to-image, imag…

cs.CV2026

MomentSeeker: A Task-Oriented Benchmark For Long-Video Moment Retrieval

Huaying Yuan, Jian Ni, Zheng Liu +7

Accurately locating key moments within long videos is crucial for solving long video understanding (LVU) tasks. However, existing benchmarks are either severely limited in terms of…

cs.CV2025

VideoExplorer: Think With Videos For Agentic Long-Video Understanding

Huaying Yuan, Zheng Liu, Junjie Zhou +5

Long-video understanding~(LVU) is a challenging problem in computer vision. Existing methods either downsample frames for single-pass reasoning, sacrificing fine-grained details, o…

cs.IR2025

MR-Bench: Going Beyond Matching to Reasoning in Multimodal Retrieval

Junjie Zhou, Ze Liu, Lei Xiong +10

Multimodal retrieval is becoming a crucial component of modern AI applications, yet its evaluation lags behind the demands of more realistic and challenging scenarios. Existing ben…

cs.CV2025

Task-Aware KV Compression For Cost-Effective Long Video Understanding

Minghao Qin, Yan Shu, Peitian Zhang +6

Long-video understanding (LVU) remains a severe challenge for existing multimodal large language models (MLLMs), primarily due to the prohibitive computational cost. Recent approac…

cs.CV2025

Video-XL-2: Towards Very Long-Video Understanding Through Task-Aware KV Sparsification

Minghao Qin, Xiangrui Liu, Zhengyang Liang +6

Multi-modal large language models (MLLMs) models have made significant progress in video understanding over the past few years. However, processing long video inputs remains a majo…