Efficient Human behavior understanding_3d pose estimate
- 논문 하루에 하나씩
논문을 공부하고 HMR을 기반으로하여, 백본 네트워크를 본인의 아이디어로 아키텍처를 재구성하고 학습시켜 성능을 유지하면서 속도 올리기(RealTime)
- Single Image 기반 Human Mesh Recovery에서 더 도전적으로 [VIBE, CVPR2020]
- Bounding Box를 detection하면서 동시에 human mesh recovery가 가능한 형태로 Mask R-CNN이나 Yolo등의 Two/One stage방법등으로 확장 시도
- SMPL:A Skinned Multi-Person Linear Model, ACM Trans. Graphics (Proc. SIGGRAPH Asia), 2015
- Keep it {SMPL}: Automatic Estimation of {3D} Human Pose and Shape from a Single Image, ECCV 2016
- End-to-end Recovery of Human Shape and Pose, CVPR 2018 참고
- Learning to Reconstruct 3D Human Pose and Shape via Model-fitting in the Loop, ICCV 2019 참고
- VIBE: Video Inference for Human Body Pose and Shape Estimation, CVPR 2020
- End-to-End Human Pose and Mesh Reconstruction with Transformers, CVPR 2021 참고
- Mask R-CNN, ICCV 2017
- Focal Loss for Dense Object Detection, ICCV 2017(RetinaNet)
- YOLACT:Real-time Instance Segmentation, ICCV 2019
- MobileNets: Efficient Convolutional Neural Neetworks for Mobile Vision Applications, arXiv 2017
- CONVOLUTIONAL NEURAL NETWORKS WITH LOWRANK REGULARIZATION, ICLR 2016