Search Results for author:
Found 2 papers, 2 papers with code
Transformer-based Selective Super-Resolution for Efficient Image Refinement
Conventional super-resolution methods suffer from two drawbacks: substantial computational cost in upscaling an entire large image, and the introduction of extraneous or potentially detrimental information for downstream computer vision tasks during the refinement of the background.
Patch-based Selection and Refinement for Early Object Detection
Early object detection (OD) is a crucial task for the safety of many dynamic systems.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
