90 citations · 193 across the 14 of their papers we have counts for
14 papers
Beyond Domain Gap: Exploiting Subjectivity in Sketch-Based Person Retrieval
Kejun Lin, Zhixiang Wang, Zheng Wang +2
Person re-identification (re-ID) requires densely distributed cameras. In practice, the person of interest may not be captured by cameras and, therefore, needs to be retrieved usin…
Revisiting and Advancing Adversarial Training Through A Simple Baseline
Hong Liu
In this paper, we delve into the essential components of adversarial training which is a pioneering defense technique against adversarial attacks. We indicate that some factors suc…
The 3rd Anti-UAV Workshop & Challenge: Methods and Results
Jian Zhao, Jianan Li, Lei Jin +20
The 3rd Anti-UAV Workshop & Challenge aims to encourage research in developing novel and accurate methods for multi-scale object tracking. The Anti-UAV dataset used for the Anti-UA…
Toward Verifiable and Reproducible Human Evaluation for Text-to-Image Generation
Mayu Otani, Riku Togashi, Yu Sawai +5
Human evaluation is critical for validating the performance of text-to-image generative models, as this highly cognitive process requires deep comprehension of text and images. How…
Certified Zeroth-order Black-Box Defense with Robust UNet Denoiser
Astha Verma, A V Subramanyam, Siddhesh Bangar +3
Certified defense methods against adversarial perturbations have been recently investigated in the black-box setting with a zeroth-order (ZO) perspective. However, these methods su…
DisCO: Portrait Distortion Correction with Perspective-Aware 3D GANs
Zhixiang Wang, Yu-Lun Liu, Jia-Bin Huang +4
Close-up facial images captured at short distances often suffer from perspective distortion, resulting in exaggerated facial features and unnatural/unattractive appearances. We pro…
HOTCOLD Block: Fooling Thermal Infrared Detectors with a Novel Wearable Design
Hui Wei, Zhixiang Wang, Xuemei Jia +4
Adversarial attacks on thermal infrared imaging expose the risk of related applications. Estimating the security of these systems is essential for safely deploying them in the real…
Self-distillation with Online Diffusion on Batch Manifolds Improves Deep Metric Learning
Zelong Zeng, Fan Yang, Hong Liu +1
Recent deep metric learning (DML) methods typically leverage solely class labels to keep positive samples far away from negative ones. However, this type of method normally ignores…
Multiple Object Tracking from appearance by hierarchically clustering tracklets
Andreu Girbau, Ferran Marqués, Shin'ichi Satoh
Current approaches in Multiple Object Tracking (MOT) rely on the spatio-temporal coherence between detections combined with object appearance to match objects from consecutive fram…
Physical Adversarial Attack meets Computer Vision: A Decade Survey
Hui Wei, Hao Tang, Xuemei Jia +6
Despite the impressive achievements of Deep Neural Networks (DNNs) in computer vision, their vulnerability to adversarial attacks remains a critical concern. Extensive research has…
Reference-Guided Texture and Structure Inference for Image Inpainting
Taorong Liu, Liang Liao, Zheng Wang +1
Existing learning-based image inpainting methods are still in challenge when facing complex semantic environments and diverse hole patterns. The prior information learned from the…
Improving Generalization of Metric Learning via Listwise Self-distillation
Zelong Zeng, Fan Yang, Zheng Wang +1
Most deep metric learning (DML) methods employ a strategy that forces all positive samples to be close in the embedding space while keeping them away from negative ones. However, s…
Unsupervised Foggy Scene Understanding via Self Spatial-Temporal Label Diffusion
Liang Liao, Wenyi Chen, Jing Xiao +3
Understanding foggy image sequence in the driving scenes is critical for autonomous driving, but it remains a challenging task due to the difficulty in collecting and annotating re…
Geo-Localization via Ground-to-Satellite Cross-View Image Retrieval
Zelong Zeng, Zheng Wang, Fan Yang +1
The large variation of viewpoint and irrelevant content around the target always hinder accurate image retrieval and its subsequent tasks. In this paper, we investigate an extremel…