111 citations · 371 across the 8 of their papers we have counts for
8 papers
Consistent 3D Hand Reconstruction in Video via self-supervised Learning
Zhigang Tu, Zhisheng Huang, Yujin Chen +4
We present a method for reconstructing accurate and consistent 3D hands from a monocular video. We observe that detected 2D hand keypoints and the image texture provide important c…
Animatable Neural Radiance Fields from Monocular RGB Videos
Jianchuan Chen, Ying Zhang, Di Kang +4
We present animatable neural radiance fields (animatable NeRF) for detailed human avatar creation from monocular videos. Our approach extends neural radiance fields (NeRF) to the d…
Model-based 3D Hand Reconstruction via Self-Supervised Learning
Yujin Chen, Zhigang Tu, Di Kang +5
Reconstructing a 3D hand from a single-view RGB image is challenging due to various hand configurations and depth ambiguity. To reliably reconstruct a 3D hand from a monocular imag…
High-Fidelity 3D Digital Human Head Creation from RGB-D Selfies
Linchao Bao, Xiangkai Lin, Yajing Chen +9
We present a fully automatic system that can produce high-fidelity, photo-realistic 3D digital human heads with a consumer RGB-D selfie camera. The system only needs the user to ta…
Joint Hand-object 3D Reconstruction from a Single Image with Cross-branch Feature Fusion
Yujin Chen, Zhigang Tu, Di Kang +4
Accurate 3D reconstruction of the hand and object shape from a hand-object image is important for understanding human-object interaction as well as human daily activities. Differen…
Crowd Counting by Adaptively Fusing Predictions from an Image Pyramid
Di Kang, Antoni Chan
Because of the powerful learning capability of deep neural networks, counting performance via density map estimation has improved significantly during the past several years. Howev…
Beyond Counting: Comparisons of Density Maps for Crowd Analysis Tasks - Counting, Detection, and Tracking
Di Kang, Zheng Ma, Antoni B. Chan
For crowded scenes, the accuracy of object-based computer vision methods declines when the images are low-resolution and objects have severe occlusions. Taking counting methods for…
Crowd Counting by Adapting Convolutional Neural Networks with Side Information
Di Kang, Debarun Dhar, Antoni B. Chan
Computer vision tasks often have side information available that is helpful to solve the task. For example, for crowd counting, the camera perspective (e.g., camera angle and heigh…