45 citations · 61 across the 11 of their papers we have counts for
9 papers · 1 filter
All-pairs Consistency Learning for Weakly Supervised Semantic Segmentation
Weixuan Sun, Yanhao Zhang, Zhen Qin +5
In this work, we propose a new transformer-based regularization to better localize objects for Weakly supervised semantic segmentation (WSSS). In image-level WSSS, Class Activation…
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…
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…
Learning Audio-Visual Source Localization via False Negative Aware Contrastive Learning
Weixuan Sun, Jiayi Zhang, Jianyuan Wang +6
Self-supervised audio-visual source localization aims to locate sound-source objects in video frames without extra annotations. Recent methods often approach this goal with the hel…
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…