16 citations · 28 across the 6 of their papers we have counts for
6 papers · 1 filter
MVHM: A Large-Scale Multi-View Hand Mesh Benchmark for Accurate 3D Hand Pose Estimation
Liangjian Chen, Shih-Yao Lin, Yusheng Xie +2
Estimating 3D hand poses from a single RGB image is challenging because depth ambiguity leads the problem ill-posed. Training hand pose estimators with 3D hand mesh annotations and…
Temporal-Aware Self-Supervised Learning for 3D Hand Pose and Mesh Estimation in Videos
Liangjian Chen, Shih-Yao Lin, Yusheng Xie +2
Estimating 3D hand pose directly from RGB imagesis challenging but has gained steady progress recently bytraining deep models with annotated 3D poses. Howeverannotating 3D poses is…
DGGAN: Depth-image Guided Generative Adversarial Networks for Disentangling RGB and Depth Images in 3D Hand Pose Estimation
Liangjian Chen, Shih-Yao Lin, Yusheng Xie +3
Estimating3D hand poses from RGB images is essentialto a wide range of potential applications, but is challengingowing to substantial ambiguity in the inference of depth in-formati…
MM-Hand: 3D-Aware Multi-Modal Guided Hand Generative Network for 3D Hand Pose Synthesis
Zhenyu Wu, Duc Hoang, Shih-Yao Lin +5
Estimating the 3D hand pose from a monocular RGB image is important but challenging. A solution is training on large-scale RGB hand images with accurate 3D hand keypoint annotation…
Learning Conditional Random Fields with Augmented Observations for Partially Observed Action Recognition
Shih-Yao Lin, Yen-Yu Lin, Chu-Song Chen +1
This paper aims at recognizing partially observed human actions in videos. Action videos acquired in uncontrolled environments often contain corrupt frames, which make actions part…
Generating Realistic Training Images Based on Tonality-Alignment Generative Adversarial Networks for Hand Pose Estimation
Liangjian Chen, Shih-Yao Lin, Yusheng Xie +5
Hand pose estimation from a monocular RGB image is an important but challenging task. The main factor affecting its performance is the lack of a sufficiently large training dataset…