most citedU-Bench: A Comprehensive Understanding of U-Net through 100-Variant Benchmarking

1 citations · 1 across the 5 of their papers we have counts for

collaborators
Showing cs.CVShow all

9 papers · 1 filter

cs.CV2026

MotionAtlas: Detailed Region Captioning for Motion-Centric Videos

Weisong Liu, Haochen Wang, Kuan Gao +8

We propose MotionAtlas, a system for detailed captioning of motion-centric videos, comprising (1) a dedicated human-annotated benchmark, (2) a scalable, high-quality pipeline to co…

cs.CV2025

PEOD: A Pixel-Aligned Event-RGB Benchmark for Object Detection under Challenging Conditions

Luoping Cui, Hanqing Liu, Mingjie Liu +4

Robust object detection for challenging scenarios increasingly relies on event cameras, yet existing Event-RGB datasets remain constrained by sparse coverage of extreme conditions…

cs.CV20251 cited

U-Bench: A Comprehensive Understanding of U-Net through 100-Variant Benchmarking

Fenghe Tang, Chengqi Dong, Wenxin Ma +7

Over the past decade, U-Net has been the dominant architecture in medical image segmentation, leading to the development of thousands of U-shaped variants. Despite its widespread a…

cs.CV2025

Grasp Any Region: Towards Precise, Contextual Pixel Understanding for Multimodal LLMs

Haochen Wang, Yuhao Wang, Tao Zhang +13

While Multimodal Large Language Models (MLLMs) excel at holistic understanding, they struggle in capturing the dense world with complex scenes, requiring fine-grained analysis of i…

cs.CV2025

Foggy Crowd Counting: Combining Physical Priors and KAN-Graph

Yuhao Wang, Zhuoran Zheng, Han Hu +3

Aiming at the key challenges of crowd counting in foggy environments, such as long-range target blurring, local feature degradation, and image contrast attenuation, this paper prop…

cs.CV2025

UniConvNet: Expanding Effective Receptive Field while Maintaining Asymptotically Gaussian Distribution for ConvNets of Any Scale

Yuhao Wang, Wei Xi

Convolutional neural networks (ConvNets) with large effective receptive field (ERF), still in their early stages, have demonstrated promising effectiveness while constrained by hig…