activity
20212024
most citedFreeSeg: Unified, Universal and Open-Vocabulary Image Segmentation

10 citations · 31 across the 17 of their papers we have counts for

collaborators

17 papers

cs.CV2024

DSMix: Distortion-Induced Sensitivity Map Based Pre-training for No-Reference Image Quality Assessment

Jinsong Shi, Pan Gao, Xiaojiang Peng +1

Image quality assessment (IQA) has long been a fundamental challenge in image understanding. In recent years, deep learning-based IQA methods have shown promising performance. Howe…

cs.CV20231 cited

Generalizable Person Search on Open-world User-Generated Video Content

Junjie Li, Guanshuo Wang, Yichao Yan +5

Person search is a challenging task that involves detecting and retrieving individuals from a large set of un-cropped scene images. Existing person search applications are mostly t…

cs.CV2023

SIDE: Self-supervised Intermediate Domain Exploration for Source-free Domain Adaptation

Jiamei Liu, Han Sun, Yizhen Jia +3

Domain adaptation aims to alleviate the domain shift when transferring the knowledge learned from the source domain to the target domain. Due to privacy issues, source-free domain…

cs.CV2023

DiffusionEngine: Diffusion Model is Scalable Data Engine for Object Detection

Manlin Zhang, Jie Wu, Yuxi Ren +7

Data is the cornerstone of deep learning. This paper reveals that the recently developed Diffusion Model is a scalable data engine for object detection. Existing methods for scalin…

cs.CV2023

Unilaterally Aggregated Contrastive Learning with Hierarchical Augmentation for Anomaly Detection

Guodong Wang, Yunhong Wang, Jie Qin +3

Anomaly detection (AD), aiming to find samples that deviate from the training distribution, is essential in safety-critical applications. Though recent self-supervised learning bas…

cs.CV20232 cited

AlignDet: Aligning Pre-training and Fine-tuning in Object Detection

Ming Li, Jie Wu, Xionghui Wang +6

The paradigm of large-scale pre-training followed by downstream fine-tuning has been widely employed in various object detection algorithms. In this paper, we reveal discrepancies…