18 citations · 53 across the 9 of their papers we have counts for
8 papers · 1 filter
Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?
Pedro R. A. S. Bassi, Wenxuan Li, Yucheng Tang +50
How can we test AI performance? This question seems trivial, but it isn't. Standard benchmarks often have problems such as in-distribution and small-size test sets, oversimplified…
Video-XL: Extra-Long Vision Language Model for Hour-Scale Video Understanding
Yan Shu, Zheng Liu, Peitian Zhang +5
Long video understanding poses a significant challenge for current Multi-modal Large Language Models (MLLMs). Notably, the MLLMs are constrained by their limited context lengths an…
OmniGen: Unified Image Generation
Shitao Xiao, Yueze Wang, Junjie Zhou +7
The emergence of Large Language Models (LLMs) has unified language generation tasks and revolutionized human-machine interaction. However, in the realm of image generation, a unifi…
MLVU: Benchmarking Multi-task Long Video Understanding
Junjie Zhou, Yan Shu, Bo Zhao +9
The evaluation of Long Video Understanding (LVU) performance poses an important but challenging research problem. Despite previous efforts, the existing video understanding benchma…
M3D: Advancing 3D Medical Image Analysis with Multi-Modal Large Language Models
Fan Bai, Yuxin Du, Tiejun Huang +2
Medical image analysis is essential to clinical diagnosis and treatment, which is increasingly supported by multi-modal large language models (MLLMs). However, previous research ha…
Pushing Auto-regressive Models for 3D Shape Generation at Capacity and Scalability
Xuelin Qian, Yu Wang, Simian Luo +9
Auto-regressive models have achieved impressive results in 2D image generation by modeling joint distributions in grid space. In this paper, we extend auto-regressive models to 3D…
Efficient Multimodal Learning from Data-centric Perspective
Muyang He, Yexin Liu, Boya Wu +4
Multimodal Large Language Models (MLLMs) have demonstrated notable capabilities in general visual understanding and reasoning tasks. However, their deployment is hindered by substa…
SegVol: Universal and Interactive Volumetric Medical Image Segmentation
Yuxin Du, Fan Bai, Tiejun Huang +1
Precise image segmentation provides clinical study with instructive information. Despite the remarkable progress achieved in medical image segmentation, there is still an absence o…