no code implementations • 21 May 2024 • Jia Gong, Shenyu Ji, Lin Geng Foo, Kang Chen, Hossein Rahmani, Jun Liu
To generate high-quality garments for each layer, we introduce a coarse-to-fine strategy for diverse garment generation and a novel dual-SDS loss function to maintain coherence between the generated garments and avatar components, including the human body and other garments.
no code implementations • 1 Apr 2024 • Jia Gong, Lin Geng Foo, Yixuan He, Hossein Rahmani, Jun Liu
Sign Language Translation (SLT) is a challenging task that aims to translate sign videos into spoken language.
Ranked #1 on Gloss-free Sign Language Translation on PHOENIX14T
Gloss-free Sign Language Translation Sign Language Translation +1
no code implementations • ICCV 2023 • Lin Geng Foo, Jia Gong, Hossein Rahmani, Jun Liu
Inspired by their capability, we explore a diffusion-based approach for human mesh recovery, and propose a Human Mesh Diffusion (HMDiff) framework which frames mesh recovery as a reverse diffusion process.
no code implementations • CVPR 2023 • Lin Geng Foo, Jia Gong, Zhipeng Fan, Jun Liu
Recent years have witnessed great progress in deep neural networks for real-time applications.
1 code implementation • CVPR 2023 • Jia Gong, Lin Geng Foo, Zhipeng Fan, Qiuhong Ke, Hossein Rahmani, Jun Liu
Monocular 3D human pose estimation is quite challenging due to the inherent ambiguity and occlusion, which often lead to high uncertainty and indeterminacy.
Ranked #11 on 3D Human Pose Estimation on MPI-INF-3DHP
no code implementations • CVPR 2022 • Jia Gong, Zhipeng Fan, Qiuhong Ke, Hossein Rahmani, Jun Liu
The existing pose estimation approaches often require a large number of annotated images to attain good estimation performance, which are laborious to acquire.