ProFeat: Unsupervised Image Clustering via Progressive Feature RefinementJeonghoon Kim, Sunghoon Im, Sunghyun ChoCVPR workshop on Learning From Limited or Imperfect Data (CVPRw), 2021
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
Learning Monocular Depth in Dynamic Scenes via Instance-Aware Projection ConsistencyBest paper, Qualcomm Innovation Fellowship Korea 2020
Learning Monocular Depth in Dynamic Scenes via Instance-Aware Projection Consistency Silver Prize, 16th Samsung Electro-Mechanics Best Paper Awards
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
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 …
Sungho Moon, Jinhwoi Kim and Kyumin Hwang joined our group. Welcome all! Sungho Moon joined our lab as an Combined BS/MS/PhD course, and Jinhwoi Kim and Kyumin Hwang joined our lab as an MS course.
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
From October 27th to November 2nd, DGIST Computer Vision Lab. members attended the ICCV (International conference on Computer Vision) in Seoul, Korea.
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]