Less is More: Focus Attention for Efficient DETR

24 July 2023

Papers citing "Less is More: Focus Attention for Efficient DETR"

8 / 8 papers shown

Title
Semantics Prompting Data-Free Quantization for Low-Bit Vision Transformers Yunshan Zhong Yuyao Zhou Yuxin Zhang Shen Li Yong Li Fei Chao Zhanpeng Zeng Rongrong Ji MQ 89 0 0 31 Dec 2024
Token Pruning using a Lightweight Background Aware Vision Transformer Sudhakar Sah Ravish Kumar Honnesh Rohmetra Ehsan Saboori ViT 16 0 0 12 Oct 2024
FastTextSpotter: A High-Efficiency Transformer for Multilingual Scene Text Spotting Alloy Das Sanket Biswas Umapada Pal Josep Lladós Saumik Bhattacharya 49 2 0 27 Aug 2024
Prompt-Aware Adapter: Towards Learning Adaptive Visual Tokens for Multimodal Large Language Models Yue Zhang Hehe Fan Yi Yang 41 3 0 24 May 2024
SLAB: Efficient Transformers with Simplified Linear Attention and Progressive Re-parameterized Batch Normalization Jialong Guo Xinghao Chen Yehui Tang Yunhe Wang ViT 47 9 0 19 May 2024
YOLO-TLA: An Efficient and Lightweight Small Object Detection Model based on YOLOv5 Peng Gao Chun-Lin Ji Tao Yu Ruyue Yuan ObjD 21 34 0 22 Feb 2024
Adaptive Sparse ViT: Towards Learnable Adaptive Token Pruning by Fully Exploiting Self-Attention Xiangcheng Liu Tianyi Wu Guodong Guo ViT 40 26 0 28 Sep 2022
DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETR Shilong Liu Feng Li Hao Zhang X. Yang Xianbiao Qi Hang Su Jun Zhu Lei Zhang ViT 138 703 0 28 Jan 2022