Robotics and Computer Vision Lab

Publications

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저 자 Gyeongmin Choe, Srinivasa G. Narasimhan, In So Kweon
학 회 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) [Spotlight]
Notes This research was supported by ONR Grant N00014-14-1-0595, NSF NRI grant IIS-1317749 and the Ministry of Trade, Industry & Energy and the Korea Evaluation Institute of Industrial Technology (KEIT) with the program number of 10060110.
논문일시(Year) 2016
논문일시(Month) 06
http://rcv.kaist.ac.kr/gmchoe/Project/NISAR/Near-Infrared (NIR) images of most materials exhibit less texture or albedo variations making them beneficial for vision tasks such as intrinsic image decomposition and structured light depth estimation. Understanding the reflectance properties (BRDF) of materials in the NIR wavelength range can be further useful for many photometric methods including shape from shading and inverse rendering. However, even with less albedo variation, many materials e.g. fabrics, leaves, etc. exhibit complex fine-scale surface detail making it hard to accurately estimate BRDF. In this paper, we present an approach to simultaneously estimate NIR BRDF and fine-scale surface details by imaging materials under different IR lighting and viewing directions. This is achieved by a novel iterative scheme that alternately estimates surface detail and NIR BRDF until convergence. Our setup does not require complicated gantries or calibration and we present the first NIR dataset of 100 materials including a variety of fabrics (knits, weaves, cotton, satin, leather), and organic (skin, leaves, jute, trunk, fur) and inorganic materials (plastic, concrete, carpet). The NIR BRDFs measured from material samples are used with a shape-from-shading algorithm to demonstrate fine-scale reconstruction of objects from a single NIR image.

List of Articles
279. A Real-Time and Energy-Efficient Embedded System for Intelligent ADAS with RNN-Based Deep Risk Prediction using Stereo Camera
Kyuho Lee, Gyeongmin Choe, Kyeongryeol Bong, Changhyeon Kim, In So Kweon, Hoi-Jun Yoo
International Conference on Computer Vision Systems (ICVS) 2017 / 07
278. A Unified Approach of Multi-scale Deep and Hand-crafted Features for Defocus Estimation
Jinsun Park, Yu-Wing Tai, Donghyeon Cho, In So Kweon
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017 / 07
277. Deep Representation of Industrial Components using Simulated Images
Seong-Heum Kim, Gyeongmin Choe, Byungtae Ahn, In So Kweon
IEEE International Conference on Robotics and Automation (ICRA) 2017 / 05
276. Single Image Depth Estimation using Convolutional Neural Networks with NCC-based Loss
Jinsun Park, In So Kweon
International Workshop on Frontiers of Computer Vision (FCV) 2017 / 02
275. Robust Road Marking Detection and Recognition Using Density-Based Grouping and Machine Learning Techniques
Oleksandr Bailo, Seokju Lee, Francois Rameau, Jae Shin Yoon, In So Kweon
Winter Conference of Applications on Computer Vision (WACV) 2017 / 03
274. Control strategies for a humanoid robot to drive and then egress a utility vehicle for remote approach
Hyobin Jeong, Jaesung Oh, Mingeuk Kim, Kyungdon Joo, In So Kweon, Jun-Ho Oh
IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids) 2015 / 11
273. A Real-time Vehicular Vision System to Seamlessly See-through Cars
Francois Rameau, Hyowon Ha, Kyungdon Joo, Jinsoo Choi, In So Kweon
European Conference on Computer Vision Workshops (ECCVW - ACVR) 2016 / 10
272. A Real-time Augmented Reality System to See-Through Cars
Francois Rameau, Hyowon Ha, Kyungdon Joo, Jinsoo Choi, Kibaek Park, In So Kweon
IEEE International Symposium on Mixed and Augmented Reality (ISMAR) 2016 / 09
271. Pixel-Level Domain Transfer
Donggeun Yoo, Namil Kim, Sunggyun Park, Anthony S. Paek, In So Kweon
European Conference on Computer Vision (ECCV) 2016 / 10
270. A Pseudo-Bayesian Algorithm for Robust PCA
Tae-Hyun Oh, Yasuyuki Matsushita, In So Kweon, David Wipf
Neural Information Processing Systems (NIPS) 2016 / 12
269. Natural Image Matting using Deep Convolutional Neural Networks
Donghyeon Cho, Yu-Wing Tai, In So Kweon
European Conference on Computer Vision (ECCV), 2016 2016 / 10
268. Photometric Stereo under Non-uniform Light Intensities and Exposures
Donghyeon Cho, Yasuyuki Matsushita, Yu-Wing Tai, In So Kweon
European Conference on Computer Vision (ECCV), 2016 2016 / 10
267. Fine-scale Surface Normal Estimation using a Single NIR Image
Youngjin Yoon, Gyeongmin Choe, Namil Kim, Joon-Young Lee, In So Kweon
European Conference on Computer Vision (ECCV) , October 2016 2016 / 10
266. All-around Depth from Small Motion with A Spherical Panoramic Camera
Sunghoon Im, Hyowon Ha, Francois Rameau, Hae-Gon Jeon, Gyeongmin Choe, In So Kweon
European Conference on Computer Vision (ECCV) 2016 / 10
265. Human Body Part Classification from Optical Flow
Junsik Kim, Kyungdon Joo, Tae-Hyun Oh, In So Kweon
The International Conference on Ubiquitous Robots and Ambient Intelligence (URAI) 2016 / 08
264. Asymmetric Stereo with Catadioptric Lens: High Quality Image Generation for Intelligent Robot
Donghyeon Cho, Jinsun Park, Yu-Wing Tai, In So Kweon
The International Conference on Ubiquitous Robots and Ambient Intelligence (URAI) 2016 / 08
263. Sentence Learning on Deep Convolutional Networks for Image Caption Generation
Dong-Jin Kim, Donggeun Yoo, Bonggeun Sim, In So Kweon
The International Conference on Ubiquitous Robots and Ambient Intelligence (URAI) 2016 / 08
262. EureCar Turbo: a Self-Driving Car that can Handle Adverse Weather Conditions
Unghui Lee, Jiwon Jung, Seunghak Shin, Yongseop Jeong, Kibaek Park, David Hyunchul Shim, In So Kweon
The International Conference of Intelligent Robots and Systems (IROS) 2016 / 10
261. Object Proposal Using 3D Point Cloud for DRC-HUBO+
Seunghak Shin, Inwook Shim, Jiyoung Jung, Yunsu Bok, Jun-Ho Oh, In So Kweon
The International Conference of Intelligent Robots and Systems (IROS) 2016 / 10
260. Fast Multiple Objects Detection and Tracking Fusing Color Camera and 3D LIDAR for Intelligent Vehicles
Soonmin Hwang, Namil Kim, Yukyung Choi, Seokju Lee, In So Kweon
The International Conference on Ubiquitous Robots and Ambient Intelligence (URAI) 2016 / 08
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