Robotics and Computer Vision Lab

Publications

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저 자 Seunghak Shin, Inwook Shim, Jiyoung Jung, Yunsu Bok, Jun-Ho Oh, In So Kweon
학 회 The International Conference of Intelligent Robots and Systems (IROS)
Notes This work was supported by Ministry of Trade Industry and Energy of Republic of Korea(MOTIE) (No.10050159) and the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIP) (No.2010-0028680)
논문일시(Year) 2016
논문일시(Month) 10
We present an object proposal method which utilizes the 3D data obtained from a depth sensor as well as the color information of images. Our object proposal method is designed to improve the performance of the object detection for a mobile robot equipped with a camera and a laser scanner. Compared to traditional object proposal methods using only 2D images, the proposed method provides much less number of candidate windows for object detection. We show less than 100 object proposal windows per image using the proposed method result in high recall tested on the public dataset. Our method presents object proposals in 3D space as well as in 2D image thus it can further be applied to following tasks for mobile robots such as 3D location and pose estimation of the target object after successful object detection. We validate our method using the real-world object detection dataset for outdoor mobile robots captured during the DRC Finals 2015 and the public dataset for comparison with the previous methods.

List of Articles
359. Correlate-and-Excite: Real-Time Stereo Matching via Guided Cost Volume Excitation
Antyanta Bangunharcana, Jae Won Cho, Seokju Lee, In So Kweon, Kyung-Soo Kim, Soohyun Kim
International Conference on Intelligent Robots and Systems, IROS, 2021 2021 / 06
358. Deep Volumetric Depth Fusion for 3D Scene Reconstruction
Jaesung Choe, Sunghoon Im, Francois Rameau, Minjun Kang, and In So Kweon
IEEE International Conference on Computer Vision (ICCV) 2021 / 10
357. Attentive and Contrastive Learning for Joint Depth and Motion Field Estimation
Seokju Lee, Francois Rameau, Fei Pan, and In So Kweon
IEEE International Conference on Computer Vision (ICCV) 2021 / 10
356. LabOR: Labeling Only if Required for Domain Adaptive Semantic Segmentation
Inkyu Shin, Dong-Jin Kim, Jae Won Cho, Sanghyun Woo, Kwanyong Park, and In So Kweon
IEEE International Conference on Computer Vision (ICCV) 2021 / 10
355. Depth Completion using Plane-Residual Representation
Byeong-Uk Lee, Kyunghyun Lee and In So Kweon
Computer Vision and Pattern Recognition, CVPR, 2021 2021 / 06
354. Learning to Associate Every Segment for Video Panoptic Segmentation
Sanghyun Woo, Dahun Kim, Joon-Young Lee and In So Kweon
Computer Vision and Pattern Recognition, CVPR, 2021 2021 / 06
353. Volumetric Propagation Network: Stereo-LiDAR Fusion for Long Range Depth Estimation
Jaesung Choe, Kyungdon Joo, Imtiaz Tooba, In So Kweon
IEEE Robotics and Automation Letters (RA-L) 2021 / 06
352. Stereo Object Matching Network
{Jaesung Choe, Kyungdon Joo}*, Francois Rameau, and In So Kweon
IEEE International Conference on Robotics and Automation (ICRA) 2021 / 06
351. Universal Adversarial Perturbations Through the Lens of Deep Steganography: Towards A Fourier Perspective
{Chaoning Zhang, Philipp Benz}*, Adil Karjauv, In So Kweon
Association for the Advancement of Artificial Intelligence (AAAI) 2021 / 02
350. Optical Flow Estimation from a Single Motion-blurred Image
Dawit Mureja Argaw, Junsik Kim, Francois Rameau, Jae Won Cho, In So Kweon
Association for the Advancement of Artificial Intelligence (AAAI) 2021 / 02
349. Motion-blurred Video Interpolation and Extrapolation
Dawit Mureja Argaw, Junsik Kim, Francois Rameau, In So Kweon
Association for the Advancement of Artificial Intelligence (AAAI) 2021 / 02
348. Learning Monocular Depth in Dynamic Scenes via Instance-Aware Projection Consistency
Seokju Lee, Sunghoon Im, Stephen Lin, In So Kweon
Association for the Advancement of Artificial Intelligence (AAAI) 2021 / 02
347. ResNet or DenseNet? Introducing Dense Shortcuts to ResNet
Chaoning Zhang*, Philipp Benz*, Dawit Mureja Argaw, Seokju Lee, Junsik Kim, Francois Rameau, Jean-Charles Bazin, In So Kweon (*: equal contribution)
IEEE Winter Conference on Applications of Computer Vision (WACV) 2021 / 1
346. High-quality Frame Interpolation via Tridirectional Inference
Jinsoo Choi, Jaesik Park, and In So Kweon
IEEE Winter Conference on Applications of Computer Vision (WACV) 2021 / 01
345. Revisiting Batch Normalization for Improving Corruption Robustness
Philipp Benz*, Chaoning Zhang*, Adil Karjauv, and In So Kweon (*: equal contribution)
IEEE Winter Conference on Applications of Computer Vision (WACV) 2021 / 01
344. The Devil is in the Boundary: Exploiting Boundary Representation for Basis-based Instance Segmentation
Myungchul Kim, Sanghyun Woo, Dahun Kim, and In So Kweon
IEEE Winter Conference on Applications of Computer Vision (WACV) 2021 / 01
343. UDH: Universal Deep Hiding for Steganography, Watermarking, and Light Field Messaging
Chaoning Zhang*, Philipp Benz*, Adil Karjauv*, Geng Sun, In-So Kweon (*: equal-contribution)
NeurIPS, 2020 2020 / 12
342. Discover, Hallucinate, and Adapt: Open Compound Domain Adaptation for Semantic Segmentation
KwanYong Park, Sanghyun Woo, Inkyu Shin, In So Kweon
NeurIPS, 2020 2020 / 12
341. An Efficient Asynchronous Method for Integrating Evolutionary and Gradient-based Policy Search
Kyunghyun Lee, Byeong-Uk Lee, Ukcheol Shin, In So Kweon
NeurIPS, 2020 2020 / 12
340. Align-and-Attend Network for Globally and Locally Coherent Video Inpainting
Sanghyun Woo, Dahun Kim, KwanYong Park, Joon-Young Lee, In So Kweon
British Machine Vision Conference (BMVC) 2020 / 09
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