50 citations · 159 across the 13 of their papers we have counts for
15 papers
Generative Modeling of Shape-Dependent Self-Contact Human Poses
Takehiko Ohkawa, Jihyun Lee, Shunsuke Saito +7
One can hardly model self-contact of human poses without considering underlying body shapes. For example, the pose of rubbing a belly for a person with a low BMI leads to penetrati…
ATLAS: Decoupling Skeletal and Shape Parameters for Expressive Parametric Human Modeling
Jinhyung Park, Javier Romero, Shunsuke Saito +7
Parametric body models offer expressive 3D representation of humans across a wide range of poses, shapes, and facial expressions, typically derived by learning a basis over registe…
Relightable Full-Body Gaussian Codec Avatars
Shaofei Wang, Tomas Simon, Igor Santesteban +15
We propose Relightable Full-Body Gaussian Codec Avatars, a new approach for modeling relightable full-body avatars with fine-grained details including face and hands. The unique ch…
URHand: Universal Relightable Hands
Zhaoxi Chen, Gyeongsik Moon, Kaiwen Guo +20
Existing photorealistic relightable hand models require extensive identity-specific observations in different views, poses, and illuminations, and face challenges in generalizing t…
Multiface: A Dataset for Neural Face Rendering
Cheng-hsin Wuu, Ningyuan Zheng, Scott Ardisson +28
Photorealistic avatars of human faces have come a long way in recent years, yet research along this area is limited by a lack of publicly available, high-quality datasets covering…
CodedStereo: Learned Phase Masks for Large Depth-of-field Stereo
Shiyu Tan, Yicheng Wu, Shoou-I Yu +1
Conventional stereo suffers from a fundamental trade-off between imaging volume and signal-to-noise ratio (SNR) -- due to the conflicting impact of aperture size on both these vari…
Supervision by Registration and Triangulation for Landmark Detection
Xuanyi Dong, Yi Yang, Shih-En Wei +3
We present Supervision by Registration and Triangulation (SRT), an unsupervised approach that utilizes unlabeled multi-view video to improve the accuracy and precision of landmark…
InterHand2.6M: A Dataset and Baseline for 3D Interacting Hand Pose Estimation from a Single RGB Image
Gyeongsik Moon, Shoou-i Yu, He Wen +2
Analysis of hand-hand interactions is a crucial step towards better understanding human behavior. However, most researches in 3D hand pose estimation have focused on the isolated s…
Epipolar Transformers
Yihui He, Rui Yan, Katerina Fragkiadaki +1
A common approach to localize 3D human joints in a synchronized and calibrated multi-view setup consists of two-steps: (1) apply a 2D detector separately on each view to localize j…
Self-Supervised Adaptation of High-Fidelity Face Models for Monocular Performance Tracking
Jae Shin Yoon, Takaaki Shiratori, Shoou-I Yu +1
Improvements in data-capture and face modeling techniques have enabled us to create high-fidelity realistic face models. However, driving these realistic face models requires speci…
Supervision-by-Registration: An Unsupervised Approach to Improve the Precision of Facial Landmark Detectors
Xuanyi Dong, Shoou-I Yu, Xinshuo Weng +3
In this paper, we present supervision-by-registration, an unsupervised approach to improve the precision of facial landmark detectors on both images and video. Our key observation…
Long-Term Identity-Aware Multi-Person Tracking for Surveillance Video Summarization
Shoou-I Yu, Yi Yang, Xuanchong Li +1
Multi-person tracking plays a critical role in the analysis of surveillance video. However, most existing work focus on shorter-term (e.g. minute-long or hour-long) video sequences…
Improving Human Activity Recognition Through Ranking and Re-ranking
Zhenzhong Lan, Shoou-I Yu, Alexander G. Hauptmann
We propose two well-motivated ranking-based methods to enhance the performance of current state-of-the-art human activity recognition systems. First, as an improvement over the cla…
Handcrafted Local Features are Convolutional Neural Networks
Zhenzhong Lan, Shoou-I Yu, Ming Lin +2
Image and video classification research has made great progress through the development of handcrafted local features and learning based features. These two architectures were prop…
The Best of Both Worlds: Combining Data-independent and Data-driven Approaches for Action Recognition
Zhenzhong Lan, Dezhong Yao, Ming Lin +2
Motivated by the success of data-driven convolutional neural networks (CNNs) in object recognition on static images, researchers are working hard towards developing CNN equivalents…