Search Results for author: Kaiwen Guo

Found 16 papers, 2 papers with code

URHand: Universal Relightable Hands

no code implementations10 Jan 2024 Zhaoxi Chen, Gyeongsik Moon, Kaiwen Guo, Chen Cao, Stanislav Pidhorskyi, Tomas Simon, Rohan Joshi, Yuan Dong, Yichen Xu, Bernardo Pires, He Wen, Lucas Evans, Bo Peng, Julia Buffalini, Autumn Trimble, Kevyn McPhail, Melissa Schoeller, Shoou-I Yu, Javier Romero, Michael Zollhöfer, Yaser Sheikh, Ziwei Liu, Shunsuke Saito

To simplify the personalization process while retaining photorealism, we build a powerful universal relightable prior based on neural relighting from multi-view images of hands captured in a light stage with hundreds of identities.

Grouped Knowledge Distillation for Deep Face Recognition

no code implementations10 Apr 2023 Weisong Zhao, Xiangyu Zhu, Kaiwen Guo, Xiao-Yu Zhang, Zhen Lei

Therefore, we seek to probe the target logits to extract the primary knowledge related to face identity, and discard the others, to make the distillation more achievable for the student network.

Face Recognition Knowledge Distillation

Drivable Volumetric Avatars using Texel-Aligned Features

no code implementations20 Jul 2022 Edoardo Remelli, Timur Bagautdinov, Shunsuke Saito, Tomas Simon, Chenglei Wu, Shih-En Wei, Kaiwen Guo, Zhe Cao, Fabian Prada, Jason Saragih, Yaser Sheikh

To circumvent this, we propose a novel volumetric avatar representation by extending mixtures of volumetric primitives to articulated objects.

Geometry-aware Single-image Full-body Human Relighting

no code implementations11 Jul 2022 Chaonan Ji, Tao Yu, Kaiwen Guo, Jingxin Liu, Yebin Liu

For the relighting, we introduce a ray tracing-based per-pixel lighting representation that explicitly models high-frequency shadows and propose a learning-based shading refinement module to restore realistic shadows (including hard cast shadows) from the ray-traced shading maps.

Disentanglement Neural Rendering

POSEFusion: Pose-guided Selective Fusion for Single-view Human Volumetric Capture

no code implementations CVPR 2021 Zhe Li, Tao Yu, Zerong Zheng, Kaiwen Guo, Yebin Liu

By contributing a novel reconstruction framework which contains pose-guided keyframe selection and robust implicit surface fusion, our method fully utilizes the advantages of both tracking-based methods and tracking-free inference methods, and finally enables the high-fidelity reconstruction of dynamic surface details even in the invisible regions.

3D Reconstruction

HumanGPS: Geodesic PreServing Feature for Dense Human Correspondences

1 code implementation CVPR 2021 Feitong Tan, Danhang Tang, Mingsong Dou, Kaiwen Guo, Rohit Pandey, Cem Keskin, Ruofei Du, Deqing Sun, Sofien Bouaziz, Sean Fanello, Ping Tan, yinda zhang

In this paper, we address the problem of building dense correspondences between human images under arbitrary camera viewpoints and body poses.

NeuralHumanFVV: Real-Time Neural Volumetric Human Performance Rendering using RGB Cameras

no code implementations CVPR 2021 Xin Suo, Yuheng Jiang, Pei Lin, Yingliang Zhang, Kaiwen Guo, Minye Wu, Lan Xu

4D reconstruction and rendering of human activities is critical for immersive VR/AR experience. Recent advances still fail to recover fine geometry and texture results with the level of detail present in the input images from sparse multi-view RGB cameras.

4D reconstruction Multi-Task Learning

HybridFusion: Real-Time Performance Capture Using a Single Depth Sensor and Sparse IMUs

no code implementations ECCV 2018 Zerong Zheng, Tao Yu, Hao Li, Kaiwen Guo, Qionghai Dai, Lu Fang, Yebin Liu

We propose a light-weight and highly robust real-time human performance capture method based on a single depth camera and sparse inertial measurement units (IMUs).

Surface Reconstruction

DDRNet: Depth Map Denoising and Refinement for Consumer Depth Cameras Using Cascaded CNNs

3 code implementations ECCV 2018 Shi Yan, Chenglei Wu, Lizhen Wang, Feng Xu, Liang An, Kaiwen Guo, Yebin Liu

Consumer depth sensors are more and more popular and come to our daily lives marked by its recent integration in the latest Iphone X.


BodyFusion: Real-Time Capture of Human Motion and Surface Geometry Using a Single Depth Camera

no code implementations ICCV 2017 Tao Yu, Kaiwen Guo, Feng Xu, Yuan Dong, Zhaoqi Su, Jianhui Zhao, Jianguo Li, Qionghai Dai, Yebin Liu

To reduce the ambiguities of the non-rigid deformation parameterization on the surface graph nodes, we take advantage of the internal articulated motion prior for human performance and contribute a skeleton-embedded surface fusion (SSF) method.

Surface Reconstruction

FlyCap: Markerless Motion Capture Using Multiple Autonomous Flying Cameras

no code implementations29 Oct 2016 Lan Xu, Lu Fang, Wei Cheng, Kaiwen Guo, Guyue Zhou, Qionghai Dai, Yebin Liu

We propose a novel non-rigid surface registration method to track and fuse the depth of the three flying cameras for surface motion tracking of the moving target, and simultaneously calculate the pose of each flying camera.

Markerless Motion Capture Visual Odometry

Robust Non-Rigid Motion Tracking and Surface Reconstruction Using L0 Regularization

no code implementations ICCV 2015 Kaiwen Guo, Feng Xu, Yangang Wang, Yebin Liu, Qionghai Dai

We present a new motion tracking method to robustly reconstruct non-rigid geometries and motions from single view depth inputs captured by a consumer depth sensor.

Surface Reconstruction

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