2 citations · 2 across the 5 of their papers we have counts for
6 papers
LensErase: A Foundation Model for Erase Anything
Yunuo Chen, Xiuyu Wu, Qinhong Yang +11
We introduce LensErase, a general-purpose mask-based Erase Anything foundation model designed to cover a broad spectrum of real-world erase scenarios. LensErase supports diverse ob…
ANFI: Rethinking Neighbor Feature Interaction in Person Re-ID
Xulin Li, Yan Lu, Bin Liu +5
In person re-identification, neighbor-based methods have achieved significant success by interacting with neighbor samples to obtain more robust representations. However, existing…
MFEN:Multi-Frequency Expert Network for Visible-Infrared Person Re-ID
Xulin Li, Yan Lu, Bin Liu +4
Visible-infrared person re-identification (VI-ReID) is challenging due to the large modality discrepancy between visible and infrared images. We contend that this discrepancy is la…
Lens: Rethinking Training Efficiency for Foundational Text-to-Image Models
Dong Chen, Fangyun Wei, Ziyu Wan +18
We introduce Lens, a 3.8B-parameter T2I model that achieves performance competitive with, and in several cases surpassing, state-of-the-art models with more than 6B parameters acro…
Towards Anytime Retrieval: A Benchmark for Anytime Person Re-Identification
Xulin Li, Yan Lu, Bin Liu +6
In real applications, person re-identification (ReID) is expected to retrieve the target person at any time, including both daytime and nighttime, ranging from short-term to long-t…
HQ-50K: A Large-scale, High-quality Dataset for Image Restoration
Qinhong Yang, Dongdong Chen, Zhentao Tan +6
This paper introduces a new large-scale image restoration dataset, called HQ-50K, which contains 50,000 high-quality images with rich texture details and semantic diversity. We ana…