75 citations · 139 across the 15 of their papers we have counts for
6 papers · 1 filter
Be Careful with Rotation: A Uniform Backdoor Pattern for 3D Shape
Linkun Fan, Fazhi He, Qing Guo +3
For saving cost, many deep neural networks (DNNs) are trained on third-party datasets downloaded from internet, which enables attacker to implant backdoor into DNNs. In 2D domain,…
Decoupled Mixup for Generalized Visual Recognition
Haozhe Liu, Wentian Zhang, Jinheng Xie +7
Convolutional neural networks (CNN) have demonstrated remarkable performance when the training and testing data are from the same distribution. However, such trained CNN models oft…
Class-Level Confidence Based 3D Semi-Supervised Learning
Zhimin Chen, Longlong Jing, Liang Yang +2
Recent state-of-the-art method FlexMatch firstly demonstrated that correctly estimating learning status is crucial for semi-supervised learning (SSL). However, the estimation metho…
Combating Mode Collapse in GANs via Manifold Entropy Estimation
Haozhe Liu, Bing Li, Haoqian Wu +5
Generative Adversarial Networks (GANs) have shown compelling results in various tasks and applications in recent years. However, mode collapse remains a critical problem in GANs. I…
Learning Scene Flow in 3D Point Clouds with Noisy Pseudo Labels
Bing Li, Cheng Zheng, Guohao Li +1
We propose a novel scene flow method that captures 3D motions from point clouds without relying on ground-truth scene flow annotations. Due to the irregularity and sparsity of poin…
Disentangling Object Motion and Occlusion for Unsupervised Multi-frame Monocular Depth
Ziyue Feng, Liang Yang, Longlong Jing +3
Conventional self-supervised monocular depth prediction methods are based on a static environment assumption, which leads to accuracy degradation in dynamic scenes due to the misma…