307 citations · 725 across the 35 of their papers we have counts for
35 papers
Learning Photometric Feature Transform for Free-form Object Scan
Xiang Feng, Kaizhang Kang, Fan Pei +5
We propose a novel framework to automatically learn to aggregate and transform photometric measurements from multiple unstructured views into spatially distinctive and view-invaria…
A Real World Dataset for Multi-view 3D Reconstruction
Rakesh Shrestha, Siqi Hu, Minghao Gou +2
We present a dataset of 998 3D models of everyday tabletop objects along with their 847,000 real world RGB and depth images. Accurate annotations of camera poses and object poses f…
VoLux-GAN: A Generative Model for 3D Face Synthesis with HDRI Relighting
Feitong Tan, Sean Fanello, Abhimitra Meka +6
We propose VoLux-GAN, a generative framework to synthesize 3D-aware faces with convincing relighting. Our main contribution is a volumetric HDRI relighting method that can efficien…
Riggable 3D Face Reconstruction via In-Network Optimization
Ziqian Bai, Zhaopeng Cui, Xiaoming Liu +1
This paper presents a method for riggable 3D face reconstruction from monocular images, which jointly estimates a personalized face rig and per-image parameters including expressio…
Stereo Matching by Self-supervision of Multiscopic Vision
Weihao Yuan, Yazhan Zhang, Bingkun Wu +4
Self-supervised learning for depth estimation possesses several advantages over supervised learning. The benefits of no need for ground-truth depth, online fine-tuning, and better…
Learning Camera Localization via Dense Scene Matching
Shitao Tang, Chengzhou Tang, Rui Huang +2
Camera localization aims to estimate 6 DoF camera poses from RGB images. Traditional methods detect and match interest points between a query image and a pre-built 3D model. Recent…
HumanGPS: Geodesic PreServing Feature for Dense Human Correspondences
Feitong Tan, Danhang Tang, Mingsong Dou +9
In this paper, we address the problem of building dense correspondences between human images under arbitrary camera viewpoints and body poses. Prior art either assumes small motion…
AR Mapping: Accurate and Efficient Mapping for Augmented Reality
Rui Huang, Chuan Fang, Kejie Qiu +4
Augmented reality (AR) has gained increasingly attention from both research and industry communities. By overlaying digital information and content onto the physical world, AR enab…
Compact 3D Map-Based Monocular Localization Using Semantic Edge Alignment
Kejie Qiu, Shenzhou Chen, Jiahui Zhang +4
Accurate localization is fundamental to a variety of applications, such as navigation, robotics, autonomous driving, and Augmented Reality (AR). Different from incremental localiza…
Learning Efficient Photometric Feature Transform for Multi-view Stereo
Kaizhang Kang, Cihui Xie, Ruisheng Zhu +4
We present a novel framework to learn to convert the perpixel photometric information at each view into spatially distinctive and view-invariant low-level features, which can be pl…
Single-Shot is Enough: Panoramic Infrastructure Based Calibration of Multiple Cameras and 3D LiDARs
Chuan Fang, Shuai Ding, Zilong Dong +3
The integration of multiple cameras and 3D Li- DARs has become basic configuration of augmented reality devices, robotics, and autonomous vehicles. The calibration of multi-modal s…
Cluster Contrast for Unsupervised Person Re-Identification
Zuozhuo Dai, Guangyuan Wang, Weihao Yuan +3
State-of-the-art unsupervised re-ID methods train the neural networks using a memory-based non-parametric softmax loss. Instance feature vectors stored in memory are assigned pseud…
MeshMVS: Multi-View Stereo Guided Mesh Reconstruction
Rakesh Shrestha, Zhiwen Fan, Qingkun Su +3
Deep learning based 3D shape generation methods generally utilize latent features extracted from color images to encode the semantics of objects and guide the shape generation proc…
Interpretable Foreground Object Search As Knowledge Distillation
Boren Li, Po-Yu Zhuang, Jian Gu +2
This paper proposes a knowledge distillation method for foreground object search (FoS). Given a background and a rectangle specifying the foreground location and scale, FoS retriev…
Self-Supervised Human Depth Estimation from Monocular Videos
Feitong Tan, Hao Zhu, Zhaopeng Cui +3
Previous methods on estimating detailed human depth often require supervised training with `ground truth' depth data. This paper presents a self-supervised method that can be train…
LSM: Learning Subspace Minimization for Low-level Vision
Chengzhou Tang, Lu Yuan, Ping Tan
We study the energy minimization problem in low-level vision tasks from a novel perspective. We replace the heuristic regularization term with a learnable subspace constraint, and…
End-to-End Learning Local Multi-view Descriptors for 3D Point Clouds
Lei Li, Siyu Zhu, Hongbo Fu +2
In this work, we propose an end-to-end framework to learn local multi-view descriptors for 3D point clouds. To adopt a similar multi-view representation, existing studies use hand-…
Active Lighting Recurrence by Parallel Lighting Analogy for Fine-Grained Change Detection
Qian Zhang, Wei Feng, Liang Wan +3
This paper studies a new problem, namely active lighting recurrence (ALR) that physically relocalizes a light source to reproduce the lighting condition from single reference image…
Multi-View Photometric Stereo: A Robust Solution and Benchmark Dataset for Spatially Varying Isotropic Materials
Min Li, Zhenglong Zhou, Zhe Wu +3
We present a method to capture both 3D shape and spatially varying reflectance with a multi-view photometric stereo (MVPS) technique that works for general isotropic materials. Our…
Cascade Cost Volume for High-Resolution Multi-View Stereo and Stereo Matching
Xiaodong Gu, Zhiwen Fan, Zuozhuo Dai +3
The deep multi-view stereo (MVS) and stereo matching approaches generally construct 3D cost volumes to regularize and regress the output depth or disparity. These methods are limit…
Leveraging Multi-view Image Sets for Unsupervised Intrinsic Image Decomposition and Highlight Separation
Renjiao Yi, Ping Tan, Stephen Lin
We present an unsupervised approach for factorizing object appearance into highlight, shading, and albedo layers, trained by multi-view real images. To do so, we construct a multi-…
A Neural Network for Detailed Human Depth Estimation from a Single Image
Sicong Tang, Feitong Tan, Kelvin Cheng +3
This paper presents a neural network to estimate a detailed depth map of the foreground human in a single RGB image. The result captures geometry details such as cloth wrinkles, wh…
Learning Guided Convolutional Network for Depth Completion
Jie Tang, Fei-Peng Tian, Wei Feng +2
Dense depth perception is critical for autonomous driving and other robotics applications. However, modern LiDAR sensors only provide sparse depth measurement. It is thus necessary…
Joint Stabilization and Direction of 360°Videos
Chengzhou Tang, Oliver Wang, Feng Liu +1
360° video provides an immersive experience for viewers, allowing them to freely explore the world by turning their head. However, creating high-quality 360° video content can be c…