2 citations · 5 across the 9 of their papers we have counts for
8 papers · 1 filter
AnyMod-LLVE: Low-Light Video Enhancement with Modality-Agnostic Inference
Hangfeng Liang, Yutao Hu, Yanhan Hu +3
Low-light video enhancement (LLVE) remains a challenging task due to severe information degradation under low-illumination conditions. Recent multimodal approaches have significant…
Impostor: An Agent-Curated Benchmark for Realistic AIGC Manipulation Localization
Zhenliang Li, Yutao Hu, Qixiong Wang +5
Recent advances in generative image editing have improved the realism and controllability of localized image manipulation, raising new challenges for image manipulation detection a…
Learning Dense Feature Matching via Lifting Single 2D Image to 3D Space
Yingping Liang, Yutao Hu, Wenqi Shao +1
Feature matching plays a fundamental role in many computer vision tasks, yet existing methods heavily rely on scarce and clean multi-view image collections, which constrains their…
RobuSTereo: Robust Zero-Shot Stereo Matching under Adverse Weather
Yuran Wang, Yingping Liang, Yutao Hu +1
Learning-based stereo matching models struggle in adverse weather conditions due to the scarcity of corresponding training data and the challenges in extracting discriminative feat…
Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images
Yingping Liang, Ying Fu, Yutao Hu +3
Optical flow estimation is a crucial subfield of computer vision, serving as a foundation for video tasks. However, the real-world robustness is limited by animated synthetic datas…
Distilling Monocular Foundation Model for Fine-grained Depth Completion
Yingping Liang, Yutao Hu, Wenqi Shao +1
Depth completion involves predicting dense depth maps from sparse LiDAR inputs. However, sparse depth annotations from sensors limit the availability of dense supervision, which is…
Car-1000: A New Large Scale Fine-Grained Visual Categorization Dataset
Yutao Hu, Sen Li, Jincheng Yan +2
Fine-grained visual categorization (FGVC) is a challenging but significant task in computer vision, which aims to recognize different sub-categories of birds, cars, airplanes, etc.…
Beyond One-to-One: Rethinking the Referring Image Segmentation
Yutao Hu, Qixiong Wang, Wenqi Shao +4
Referring image segmentation aims to segment the target object referred by a natural language expression. However, previous methods rely on the strong assumption that one sentence…