114 citations · 299 across the 51 of their papers we have counts for
7 papers · 1 filter
Attention-based Class Activation Diffusion for Weakly-Supervised Semantic Segmentation
Jianqiang Huang, Jian Wang, Qianru Sun +1
Extracting class activation maps (CAM) is a key step for weakly-supervised semantic segmentation (WSSS). The CAM of convolution neural networks fails to capture long-range feature…
On Mitigating Hard Clusters for Face Clustering
Yingjie Chen, Huasong Zhong, Chong Chen +5
Face clustering is a promising way to scale up face recognition systems using large-scale unlabeled face images. It remains challenging to identify small or sparse face image clust…
Rethinking IoU-based Optimization for Single-stage 3D Object Detection
Hualian Sheng, Sijia Cai, Na Zhao +5
Since Intersection-over-Union (IoU) based optimization maintains the consistency of the final IoU prediction metric and losses, it has been widely used in both regression and class…
Spatial Likelihood Voting with Self-Knowledge Distillation for Weakly Supervised Object Detection
Ze Chen, Zhihang Fu, Jianqiang Huang +5
Weakly supervised object detection (WSOD), which is an effective way to train an object detection model using only image-level annotations, has attracted considerable attention fro…
Online Convolutional Re-parameterization
Mu Hu, Junyi Feng, Jiashen Hua +4
Structural re-parameterization has drawn increasing attention in various computer vision tasks. It aims at improving the performance of deep models without introducing any inferenc…
Homography Loss for Monocular 3D Object Detection
Jiaqi Gu, Bojian Wu, Lubin Fan +4
Monocular 3D object detection is an essential task in autonomous driving. However, most current methods consider each 3D object in the scene as an independent training sample, whil…