35 citations · 96 across the 16 of their papers we have counts for
31 papers · 1 filter
Energy-Based Residual Latent Transport for Unsupervised Point Cloud Completion
Ruikai Cui, Shi Qiu, Saeed Anwar +2
Unsupervised point cloud completion aims to infer the whole geometry of a partial object observation without requiring partial-complete correspondence. Differing from existing dete…
Efficient Gaussian Process Model on Class-Imbalanced Datasets for Generalized Zero-Shot Learning
Changkun Ye, Nick Barnes, Lars Petersson +1
Zero-Shot Learning (ZSL) models aim to classify object classes that are not seen during the training process. However, the problem of class imbalance is rarely discussed, despite i…
Towards Open-Set Object Detection and Discovery
Jiyang Zheng, Weihao Li, Jie Hong +2
With the human pursuit of knowledge, open-set object detection (OSOD) has been designed to identify unknown objects in a dynamic world. However, an issue with the current setting i…
Inferring the Class Conditional Response Map for Weakly Supervised Semantic Segmentation
Weixuan Sun, Jing Zhang, Nick Barnes
Image-level weakly supervised semantic segmentation (WSSS) relies on class activation maps (CAMs) for pseudo labels generation. As CAMs only highlight the most discriminative regio…
Semantic Segmentation for Real Point Cloud Scenes via Bilateral Augmentation and Adaptive Fusion
Shi Qiu, Saeed Anwar, Nick Barnes
Given the prominence of current 3D sensors, a fine-grained analysis on the basic point cloud data is worthy of further investigation. Particularly, real point cloud scenes can intu…
Weakly Supervised Video Salient Object Detection
Wangbo Zhao, Jing Zhang, Long Li +3
Significant performance improvement has been achieved for fully-supervised video salient object detection with the pixel-wise labeled training datasets, which are time-consuming an…