15 citations · 23 across the 2 of their papers we have counts for
4 papers
Scale-aware Automatic Augmentation for Object Detection
Yukang Chen, Yanwei Li, Tao Kong +4
We propose Scale-aware AutoAug to learn data augmentation policies for object detection. We define a new scale-aware search space, where both image- and box-level augmentations are…
MuCAN: Multi-Correspondence Aggregation Network for Video Super-Resolution
Wenbo Li, Xin Tao, Taian Guo +3
Video super-resolution (VSR) aims to utilize multiple low-resolution frames to generate a high-resolution prediction for each frame. In this process, inter- and intra-frames are th…
Sequential Context Encoding for Duplicate Removal
Lu Qi, Shu Liu, Jianping Shi +1
Duplicate removal is a critical step to accomplish a reasonable amount of predictions in prevalent proposal-based object detection frameworks. Albeit simple and effective, most pre…
Path Aggregation Network for Instance Segmentation
Shu Liu, Lu Qi, Haifang Qin +2
The way that information propagates in neural networks is of great importance. In this paper, we propose Path Aggregation Network (PANet) aiming at boosting information flow in pro…