16 citations · 31 across the 7 of their papers we have counts for
6 papers · 1 filter
MOS: Modeling Object-Scene Associations in Generalized Category Discovery
Zhengyuan Peng, Jinpeng Ma, Zhimin Sun +4
Generalized Category Discovery (GCD) is a classification task that aims to classify both base and novel classes in unlabeled images, using knowledge from a labeled dataset. In GCD,…
Prototype-Aware Heterogeneous Task for Point Cloud Completion
Junshu Tang, Jiachen Xu, Jingyu Gong +3
Point cloud completion, which aims at recovering original shape information from partial point clouds, has attracted attention on 3D vision community. Existing methods usually succ…
Omni-supervised Point Cloud Segmentation via Gradual Receptive Field Component Reasoning
Jingyu Gong, Jiachen Xu, Xin Tan +4
Hidden features in neural network usually fail to learn informative representation for 3D segmentation as supervisions are only given on output prediction, while this can be solved…
Face Anti-Spoofing Via Disentangled Representation Learning
Ke-Yue Zhang, Taiping Yao, Jian Zhang +6
Face anti-spoofing is crucial to security of face recognition systems. Previous approaches focus on developing discriminative models based on the features extracted from images, wh…
Novelty Detection via Non-Adversarial Generative Network
Chengwei Chen, Wang Yuan, Yuan Xie +4
One-class novelty detection is the process of determining if a query example differs from the training examples (the target class). Most of previous strategies attempt to learn the…
Anomaly Detection by One Class Latent Regularized Networks
Chengwei Chen, Pan Chen, Haichuan Song +4
Anomaly detection is a fundamental problem in computer vision area with many real-world applications. Given a wide range of images belonging to the normal class, emerging from some…