1 code implementation • ECCV 2020 • Youngjoong Kwon, Stefano Petrangeli, Dahun Kim, Haoliang Wang, Eunbyung Park, Viswanathan Swaminathan, Henry Fuchs
Second, we introduce a novel loss to explicitly enforce consistency across generated views both in space and in time.
no code implementations • 1 May 2024 • Shengze Wang, Xueting Li, Chao Liu, Matthew Chan, Michael Stengel, Josef Spjut, Henry Fuchs, Shalini De Mello, Koki Nagano
Recent breakthroughs in single-image 3D portrait reconstruction have enabled telepresence systems to stream 3D portrait videos from a single camera in real-time, potentially democratizing telepresence.
no code implementations • 10 Apr 2023 • Youngjoong Kwon, Dahun Kim, Duygu Ceylan, Henry Fuchs
We present a method that enables synthesizing novel views and novel poses of arbitrary human performers from sparse multi-view images.
no code implementations • 3 Apr 2023 • Shengze Wang, Ziheng Wang, Ryan Schmelzle, Liujie Zheng, Youngjoong Kwon, Soumyadip Sengupta, Henry Fuchs
In this paper, we work to bring telepresence to every desktop.
no code implementations • 3 Feb 2023 • Shengze Wang, Alexey Supikov, Joshua Ratcliff, Henry Fuchs, Ronald Azuma
Moreover, our discovery of natural information partition leads to a better understanding and manipulation of MLPs.
no code implementations • 22 Apr 2022 • Shengze Wang, Youngjoong Kwon, Yuan Shen, Qian Zhang, Andrei State, Jia-Bin Huang, Henry Fuchs
Experiments on the HTI dataset show that our method outperforms the baseline per-frame image fidelity and spatial-temporal consistency.
no code implementations • 5 Oct 2021 • Justin Wilson, Nicholas Rewkowski, Ming C. Lin, Henry Fuchs
Reflective and textureless surfaces such as windows, mirrors, and walls can be a challenge for object and scene reconstruction.
1 code implementation • NeurIPS 2021 • Youngjoong Kwon, Dahun Kim, Duygu Ceylan, Henry Fuchs
To tackle this, we propose Neural Human Performer, a novel approach that learns generalizable neural radiance fields based on a parametric human body model for robust performance capture.
Ranked #3 on Generalizable Novel View Synthesis on ZJU-MoCap
no code implementations • 3 Apr 2019 • Rohan Chabra, Julian Straub, Chris Sweeney, Richard Newcombe, Henry Fuchs
We propose a system that uses a convolution neural network (CNN) to estimate depth from a stereo pair followed by volumetric fusion of the predicted depth maps to produce a 3D reconstruction of a scene.
no code implementations • 21 Jan 2019 • Guoxian Song, Jianfei Cai, Tat-Jen Cham, Jianmin Zheng, Juyong Zhang, Henry Fuchs
Teleconference or telepresence based on virtual reality (VR) headmount display (HMD) device is a very interesting and promising application since HMD can provide immersive feelings for users.
no code implementations • CVPR 2015 • Mingsong Dou, Jonathan Taylor, Henry Fuchs, Andrew Fitzgibbon, Shahram Izadi
We present a 3D scanning system for deformable objects that uses only a single Kinect sensor.