16.2k citations · 17k across the 23 of their papers we have counts for
23 papers
Geo-NI: Geometry-aware Neural Interpolation for Light Field Rendering
Gaochang Wu, Yuemei Zhou, Yebin Liu +2
In this paper, we present a Geometry-aware Neural Interpolation (Geo-NI) framework for light field rendering. Previous learning-based approaches either rely on the capability of ne…
RobustFusion: Robust Volumetric Performance Reconstruction under Human-object Interactions from Monocular RGBD Stream
Zhuo Su, Lan Xu, Dawei Zhong +4
High-quality 4D reconstruction of human performance with complex interactions to various objects is essential in real-world scenarios, which enables numerous immersive VR/AR applic…
Revisiting Light Field Rendering with Deep Anti-Aliasing Neural Network
Gaochang Wu, Yebin Liu, Lu Fang +1
The light field (LF) reconstruction is mainly confronted with two challenges, large disparity and the non-Lambertian effect. Typical approaches either address the large disparity c…
Light Field Reconstruction Using Convolutional Network on EPI and Extended Applications
Gaochang Wu, Yebin Liu, Lu Fang +2
In this paper, a novel convolutional neural network (CNN)-based framework is developed for light field reconstruction from a sparse set of views. We indicate that the reconstructio…
Spatial-Angular Attention Network for Light Field Reconstruction
Gaochang Wu, Yingqian Wang, Yebin Liu +2
Typical learning-based light field reconstruction methods demand in constructing a large receptive field by deepening the network to capture correspondences between input views. In…
Zoom in to the details of human-centric videos
Guanghan Li, Yaping Zhao, Mengqi Ji +2
Presenting high-resolution (HR) human appearance is always critical for the human-centric videos. However, current imagery equipment can hardly capture HR details all the time. Exi…
SurfaceNet+: An End-to-end 3D Neural Network for Very Sparse Multi-view Stereopsis
Mengqi Ji, Jinzhi Zhang, Qionghai Dai +1
Multi-view stereopsis (MVS) tries to recover the 3D model from 2D images. As the observations become sparser, the significant 3D information loss makes the MVS problem more challen…
OccuSeg: Occupancy-aware 3D Instance Segmentation
Lei Han, Tian Zheng, Lan Xu +1
3D instance segmentation, with a variety of applications in robotics and augmented reality, is in large demands these days. Unlike 2D images that are projective observations of the…
MulayCap: Multi-layer Human Performance Capture Using A Monocular Video Camera
Zhaoqi Su, Weilin Wan, Tao Yu +4
We introduce MulayCap, a novel human performance capture method using a monocular video camera without the need for pre-scanning. The method uses "multi-layer" representations for…
PANDA: A Gigapixel-level Human-centric Video Dataset
Xueyang Wang, Xiya Zhang, Yinheng Zhu +8
We present PANDA, the first gigaPixel-level humAN-centric viDeo dAtaset, for large-scale, long-term, and multi-object visual analysis. The videos in PANDA were captured by a gigapi…
Smart Cameras
David J. Brady, Minghao Hu, Chengyu Wang +6
We review camera architecture in the age of artificial intelligence. Modern cameras use physical components and software to capture, compress and display image data. Over the past…
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke, Sam Gross, Francisco Massa +18
Deep learning frameworks have often focused on either usability or speed, but not both. PyTorch is a machine learning library that shows that these two goals are in fact compatible…
EventCap: Monocular 3D Capture of High-Speed Human Motions using an Event Camera
Lan Xu, Weipeng Xu, Vladislav Golyanik +3
The high frame rate is a critical requirement for capturing fast human motions. In this setting, existing markerless image-based methods are constrained by the lighting requirement…
LapEPI-Net: A Laplacian Pyramid EPI structure for Learning-based Dense Light Field Reconstruction
Gaochang Wu, Yebin Liu, Lu Fang +1
For dense sampled light field (LF) reconstruction problem, existing approaches focus on a depth-free framework to achieve non-Lambertian performance. However, they trap in the trad…
SPI-Optimizer: an integral-Separated PI Controller for Stochastic Optimization
Dan Wang, Mengqi Ji, Yong Wang +2
To overcome the oscillation problem in the classical momentum-based optimizer, recent work associates it with the proportional-integral (PI) controller, and artificially adds D ter…
RegNet: Learning the Optimization of Direct Image-to-Image Pose Registration
Lei Han, Mengqi Ji, Lu Fang +1
Direct image-to-image alignment that relies on the optimization of photometric error metrics suffers from limited convergence range and sensitivity to lighting conditions. Deep lea…
CrossNet: An End-to-end Reference-based Super Resolution Network using Cross-scale Warping
Haitian Zheng, Mengqi Ji, Haoqian Wang +2
The Reference-based Super-resolution (RefSR) super-resolves a low-resolution (LR) image given an external high-resolution (HR) reference image, where the reference image and LR ima…
Beyond SIFT using Binary features for Loop Closure Detection
Lei Han, Guyue Zhou, Lan Xu +1
In this paper a binary feature based Loop Closure Detection (LCD) method is proposed, which for the first time achieves higher precision-recall (PR) performance compared with state…
SurfaceNet: An End-to-end 3D Neural Network for Multiview Stereopsis
Mengqi Ji, Juergen Gall, Haitian Zheng +2
This paper proposes an end-to-end learning framework for multiview stereopsis. We term the network SurfaceNet. It takes a set of images and their corresponding camera parameters as…
MILD: Multi-Index hashing for Loop closure Detection
Lei Han, Lu Fang
Loop Closure Detection (LCD) has been proved to be extremely useful in global consistent visual Simultaneously Localization and Mapping (SLAM) and appearance-based robot relocaliza…
FlyCap: Markerless Motion Capture Using Multiple Autonomous Flying Cameras
Lan Xu, Lu Fang, Wei Cheng +4
Aiming at automatic, convenient and non-instrusive motion capture, this paper presents a new generation markerless motion capture technique, the FlyCap system, to capture surface m…
Deep Learning for Surface Material Classification Using Haptic And Visual Information
Haitian Zheng, Lu Fang, Mengqi Ji +3
When a user scratches a hand-held rigid tool across an object surface, an acceleration signal can be captured, which carries relevant information about the surface. More importantl…
Learning High-level Prior with Convolutional Neural Networks for Semantic Segmentation
Haitian Zheng, Yebin Liu, Mengqi Ji +2
This paper proposes a convolutional neural network that can fuse high-level prior for semantic image segmentation. Motivated by humans' vision recognition system, our key design is…