64 citations · 81 across the 4 of their papers we have counts for
4 papers
DetCLIP: Dictionary-Enriched Visual-Concept Paralleled Pre-training for Open-world Detection
Lewei Yao, Jianhua Han, Youpeng Wen +6
Open-world object detection, as a more general and challenging goal, aims to recognize and localize objects described by arbitrary category names. The recent work GLIP formulates t…
G-DetKD: Towards General Distillation Framework for Object Detectors via Contrastive and Semantic-guided Feature Imitation
Lewei Yao, Renjie Pi, Hang Xu +3
In this paper, we investigate the knowledge distillation (KD) strategy for object detection and propose an effective framework applicable to both homogeneous and heterogeneous stud…
Joint-DetNAS: Upgrade Your Detector with NAS, Pruning and Dynamic Distillation
Lewei Yao, Renjie Pi, Hang Xu +3
We propose Joint-DetNAS, a unified NAS framework for object detection, which integrates 3 key components: Neural Architecture Search, pruning, and Knowledge Distillation. Instead o…
SM-NAS: Structural-to-Modular Neural Architecture Search for Object Detection
Lewei Yao, Hang Xu, Wei Zhang +2
The state-of-the-art object detection method is complicated with various modules such as backbone, feature fusion neck, RPN and RCNN head, where each module may have different desi…