Jeonghoon’s paper has been accepted to CVPRw
ProFeat: Unsupervised Image Clustering via Progressive Feature RefinementJeonghoon Kim, Sunghoon Im, Sunghyun ChoCVPR workshop on Learning From Limited or Imperfect Data (CVPRw), 2021
Seunghun’s paper has been accepted to CVPR
DRANet: Disentangling Representation and Adaptation Networks for Unsupervised Cross-Domain AdaptationSeunghun Lee, Sunghyun Cho, Sunghoon ImIEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021 Article : http://www.aitimes.com/news/articleView.html?idxno=139612
Our paper has been accepted to AAAI
Learning Monocular Depth in Dynamic Scenes via Instance-Aware Projection ConsistencySeokju Lee, Sunghoon Im, Stephen Lin, In So KweonThe Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI), 2021
Our paper has been accepted to NeurIPS Workshops
Instance-wise Depth and Motion Learning from Monocular VideosSeokju Lee, Sunghoon Im, Stephen Lin, In So KweonWorkshop on Machine Learning for Autonomous Driving (NeurIPS), 2020Workshop on Differentiable computer vision, graphics, and physics …
Our paper has been accepted to ICRA
Hae-Gon Jeon, Sunghoon Im, Jean Oh, Martial Hebert,“Learning Shape-based Representation for Visual Localization in Extremely Changing Conditions“IEEE International Conference on Robotics and Automation (ICRA), 2020
Our paper has been accepted to TPAMI
Sunghoon Im, Hyowon Ha, Hae-Gon Jeon, Stephen Lin, In So Kweon,“Deep Depth from Uncalibrated Small Motion Clip“IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) [PDF]
Our paper has been accepted to TIP
Hae-Gon Jeon, Jaeheung Surh, Sunghoon Im, In So Kweon ,“Ring Difference Filter for Fast and Noise Robust Depth from Focus“, IEEE Transactions Image Processing (TIP), Dec 2020 [PDF]