270 citations
- Tencent (China)CN2 papers
- Chinese University of Hong KongHK1 paper
- Dalian University of TechnologyCN1 paper
- Google (United States)US1 paper
- Harbin Institute of TechnologyCN1 paper
- Hong Kong Polytechnic UniversityHK1 paper
- Nanjing UniversityCN1 paper
- Peking UniversityCN1 paper
- Peng Cheng LaboratoryCN1 paper
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- State Administration of Cultural HeritageCN1 paper
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6 papers
Multi-Camera Collaborative Depth Prediction via Consistent Structure Estimation
Jialei Xu, Xianming Liu, Yuanchao Bai +4
Depth map estimation from images is an important task in robotic systems. Existing methods can be categorized into two groups including multi-view stereo and monocular depth estima…
Binary Neural Networks as a general-propose compute paradigm for on-device computer vision
Guhong Nie, Lirui Xiao, Menglong Zhu +6
For binary neural networks (BNNs) to become the mainstream on-device computer vision algorithm, they must achieve a superior speed-vs-accuracy tradeoff than 8-bit quantization and…
SpotPatch: Parameter-Efficient Transfer Learning for Mobile Object Detection
Keren Ye, Adriana Kovashka, Mark Sandler +3
Deep learning based object detectors are commonly deployed on mobile devices to solve a variety of tasks. For maximum accuracy, each detector is usually trained to solve one single…
GeoNet++: Iterative Geometric Neural Network with Edge-Aware Refinement for Joint Depth and Surface Normal Estimation
Xiaojuan Qi, Zhengzhe Liu, Renjie Liao +3
In this paper, we propose a geometric neural network with edge-aware refinement (GeoNet++) to jointly predict both depth and surface normal maps from a single image. Building on to…
Learning Image-adaptive 3D Lookup Tables for High Performance Photo Enhancement in Real-time
Hui Zeng, Jianrui Cai, Lida Li +2
Recent years have witnessed the increasing popularity of learning based methods to enhance the color and tone of photos. However, many existing photo enhancement methods either del…
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…