63 citations · 449 across the 39 of their papers we have counts for
10 papers · 1 filter
Transferable Attack for Semantic Segmentation
Mengqi He, Jing Zhang, Zhaoyuan Yang +3
We analysis performance of semantic segmentation models wrt. adversarial attacks, and observe that the adversarial examples generated from a source model fail to attack the target…
Model Calibration in Dense Classification with Adaptive Label Perturbation
Jiawei Liu, Changkun Ye, Shan Wang +4
For safety-related applications, it is crucial to produce trustworthy deep neural networks whose prediction is associated with confidence that can represent the likelihood of corre…
P2C: Self-Supervised Point Cloud Completion from Single Partial Clouds
Ruikai Cui, Shi Qiu, Saeed Anwar +4
Point cloud completion aims to recover the complete shape based on a partial observation. Existing methods require either complete point clouds or multiple partial observations of…
Measuring and Modeling Uncertainty Degree for Monocular Depth Estimation
Mochu Xiang, Jing Zhang, Nick Barnes +1
Effectively measuring and modeling the reliability of a trained model is essential to the real-world deployment of monocular depth estimation (MDE) models. However, the intrinsic i…
Joint Salient Object Detection and Camouflaged Object Detection via Uncertainty-aware Learning
Aixuan Li, Jing Zhang, Yunqiu Lv +4
Salient objects attract human attention and usually stand out clearly from their surroundings. In contrast, camouflaged objects share similar colors or textures with the environmen…
Weakly-supervised Contrastive Learning for Unsupervised Object Discovery
Yunqiu Lv, Jing Zhang, Nick Barnes +1
Unsupervised object discovery (UOD) refers to the task of discriminating the whole region of objects from the background within a scene without relying on labeled datasets, which b…
Contrastive Conditional Latent Diffusion for Audio-visual Segmentation
Yuxin Mao, Jing Zhang, Mochu Xiang +4
We propose a contrastive conditional latent diffusion model for audio-visual segmentation (AVS) to thoroughly investigate the impact of audio, where the correlation between audio a…
Rethinking Polyp Segmentation from an Out-of-Distribution Perspective
Ge-Peng Ji, Jing Zhang, Dylan Campbell +2
Unlike existing fully-supervised approaches, we rethink colorectal polyp segmentation from an out-of-distribution perspective with a simple but effective self-supervised learning a…
Mutual Information Regularization for Weakly-supervised RGB-D Salient Object Detection
Aixuan Li, Yuxin Mao, Jing Zhang +1
In this paper, we present a weakly-supervised RGB-D salient object detection model via scribble supervision. Specifically, as a multimodal learning task, we focus on effective mult…
Transmission-Guided Bayesian Generative Model for Smoke Segmentation
Siyuan Yan, Jing Zhang, Nick Barnes
Smoke segmentation is essential to precisely localize wildfire so that it can be extinguished in an early phase. Although deep neural networks have achieved promising results on im…