https://github.com/google-research/tensor2robot/tree/master/research/grasp2vec
Grasp2Vec: Learning Object Representations from Self-Supervised Grasping
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Replace the cat with a British Shorthair cat of the breed with bulging yellow eyes
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Grasp2Vec: Learning Object Representations from Self-Supervised Grasping
Weighted boxes fusion: Ensembling boxes from different object detection models
YOLO Nano: a Highly Compact You Only Look Once Convolutional Neural Network for Object Detection
Shape Prior Deformation for Categorical 6D Object Pose and Size Estimation
FairMOT: On the Fairness of Detection and Re-Identification in Multiple Object Tracking
R-FCN: Object Detection via Region-based Fully Convolutional Networks
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
First-Person Hand Action Benchmark with RGB-D Videos and 3D Hand Pose Annotations
PReMVOS: Proposal-generation, Refinement and Merging for Video Object Segmentation
RealFusion: 360° Reconstruction of Any Object from a Single Image
MOTChallenge 2015: Towards a Benchmark for Multi-Target Tracking
Real-Time Grasp Detection Using Convolutional Neural Networks
Boundary-Aware Segmentation Network for Mobile and Web Applications
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.