1 code implementation • 16 Jan 2025 • Hwan Heo, Jangyeong Kim, Seongyeong Lee, Jeong A Wi, Junyoung Choi, Sangjun Ahn
In this paper, we introduce \textbf{CaPa}, a carve-and-paint framework that generates high-fidelity 3D assets efficiently.
1 code implementation • CVPR 2023 • Hoseong Cho, Chanwoo Kim, Jihyeon Kim, Seongyeong Lee, Elkhan Ismayilzada, Seungryul Baek
In our framework, we insert the whole image depicting two hands, an object and their interactions as input and jointly estimate 3 information from each frame: poses of two hands, pose of an object and object types.
Ranked #4 on Action Recognition on H2O (2 Hands and Objects)
no code implementations • 11 Nov 2022 • Changhwa Lee, Junuk Cha, Hansol Lee, Seongyeong Lee, Donguk Kim, Seungryul Baek
At the same time, to obtain high-quality 2D images from 3D space, well-designed 3D-to-2D projection and image refinement are required.
no code implementations • 30 Oct 2022 • Seongyeong Lee, Hansoo Park, Dong Uk Kim, Jihyeon Kim, Muhammadjon Boboev, Seungryul Baek
The manipulated image features are then exploited to train the hand pose estimation network via the contrastive learning framework.
no code implementations • 20 Oct 2022 • Hoseong Cho, Donguk Kim, Chanwoo Kim, Seongyeong Lee, Seungryul Baek
In this challenge, we aim to estimate global 3D hand poses from the input image where two hands and an object are interacting on the egocentric viewpoint.