43 citations · 51 across the 4 of their papers we have counts for
4 papers
W2N:Switching From Weak Supervision to Noisy Supervision for Object Detection
Zitong Huang, Yiping Bao, Bowen Dong +2
Weakly-supervised object detection (WSOD) aims to train an object detector only requiring the image-level annotations. Recently, some works have managed to select the accurate boxe…
Attend to Who You Are: Supervising Self-Attention for Keypoint Detection and Instance-Aware Association
Sen Yang, Zhicheng Wang, Ze Chen +7
This paper presents a new method to solve keypoint detection and instance association by using Transformer. For bottom-up multi-person pose estimation models, they need to detect k…
General Instance Distillation for Object Detection
Xing Dai, Zeren Jiang, Zhao Wu +4
In recent years, knowledge distillation has been proved to be an effective solution for model compression. This approach can make lightweight student models acquire the knowledge e…
ThunderNet: Towards Real-time Generic Object Detection
Zheng Qin, Zeming Li, Zhaoning Zhang +4
Real-time generic object detection on mobile platforms is a crucial but challenging computer vision task. However, previous CNN-based detectors suffer from enormous computational c…