Depth-wise Plane Sweeping
DSGN++: Exploiting Visual-Spatial Relation for Stereo-based 3D Detectors
Papers with Code 아카이브
3D Object Detection From Stereo Images
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Estimating oriented 3D bounding boxes from Stereo Cameras only.
Image: You et al
기법
관련 논문에서 소개한 기법입니다. 이 태스크에서의 평가 여부는 평가 결과에서 확인하세요.
Disp R-CNN
Disp R-CNN is a 3D object detection system for stereo images. It utilizes an instance disparity estimation network (iDispNet) that predicts disparity only for pixels on objects of interest and learns a category-specific shape prior for more accurate disparity estimation. To address the challenge from scarcity of disparity annotation in training, a statistical shape model is used to generate dense disparity pseudo-ground-truth without the need of LiDAR point clouds.
Disp R-CNN: Stereo 3D Object Detection via Shape Prior Guided Instance Disparity Estimation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.