Mixed Supervision for Instance Learning in Object Detection with Few-shot Annotation
Author:
Affiliation:
1. Sun Yat-Sen University, Guangzhou, China
2. AI Application Research Center, Huawei, Shenzhen, China
3. Pengcheng Laboratory, Shenzhen, China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3503161.3548242
Reference40 articles.
1. Multiscale Combinatorial Grouping
2. Many-Shot from Low-Shot: Learning to Annotate Using Mixed Supervision for Object Detection
3. Weakly Supervised Deep Detection Networks
4. Ze Chen , Zhihang Fu , Jianqiang Huang , Mingyuan Tao , Rongxin Jiang , Xiang Tian , Yaowu Chen , and Xian-Sheng Hua . 2021. Spatial likelihood voting with self-knowledge distillation for weakly supervised object detection. Image and Vision Computing ( 2021 ), 104314. Ze Chen, Zhihang Fu, Jianqiang Huang, Mingyuan Tao, Rongxin Jiang, Xiang Tian, Yaowu Chen, and Xian-Sheng Hua. 2021. Spatial likelihood voting with self-knowledge distillation for weakly supervised object detection. Image and Vision Computing (2021), 104314.
5. High-Quality Proposals for Weakly Supervised Object Detection
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