Search Results for author:
Found 4 papers, 4 papers with code
Fast Fourier Convolution
FFC is a generic operator that can directly replace vanilla convolutions in a large body of existing networks, without any adjustments and with comparable complexity metrics (e. g., FLOPs).
Deep High-Resolution Representation Learning for Visual Recognition
High-resolution representations are essential for position-sensitive vision problems, such as human pose estimation, semantic segmentation, and object detection.
Ranked #1 on
Object Detection
on COCO test-dev
(Hardware Burden metric)
High-Resolution Representations for Labeling Pixels and Regions
The proposed approach achieves superior results to existing single-model networks on COCO object detection.
Ranked #5 on
Semantic Segmentation
on LIP val
Acquisition of Localization Confidence for Accurate Object Detection
The network acquires this confidence of localization, which improves the NMS procedure by preserving accurately localized bounding boxes.
Ranked #185 on
Object Detection
on COCO test-dev
