Rank-DETR for high quality object detection

Y Pu, W Liang, Y Hao, Y Yuan… - Advances in …, 2023‏ - proceedings.neurips.cc
Modern detection transformers (DETRs) use a set of object queries to predict a list of
bounding boxes, sort them by their classification confidence scores, and select the top …

Mask frozen-detr: High quality instance segmentation with one gpu

Z Liang, Y Yuan - ar**_Autonomous_Driving_Radars_with_Self-Supervised_Learning_CVPR_2024_paper.pdf" data-clk="hl=fa&sa=T&oi=gga&ct=gga&cd=2&d=1705637719922915525&ei=oSO-Z-DiG5-_6rQP3vnx8Qk" data-clk-atid="xTiDK3ikqxcJ" target="_blank">[PDF] thecvf.com

Bootstrap** Autonomous Driving Radars with Self-Supervised Learning

Y Hao, S Madani, J Guan, M Alloulah… - Proceedings of the …, 2024‏ - openaccess.thecvf.com
The perception of autonomous vehicles using radars has attracted increased research
interest due its ability to operate in fog and bad weather. However training radar models is …

Cross-domain and Cross-dimension Learning for Image-to-Graph Transformers

AH Berger, L Lux, S Shit, I Ezhov, G Kaissis… - arxiv preprint arxiv …, 2024‏ - arxiv.org
Direct image-to-graph transformation is a challenging task that involves solving object
detection and relationship prediction in a single model. Due to this task's complexity, large …