Wouter Van Gansbeke
Title
Cited by
Cited by
Year
Sparse and noisy lidar completion with rgb guidance and uncertainty
W Van Gansbeke, D Neven, B De Brabandere, L Van Gool
2019 16th international conference on machine vision applications (MVA), 1-6, 2019
1172019
SCAN: Learning to Classify Images without Labels
W Van Gansbeke, S Vandenhende, S Georgoulis, M Proesmans, ...
Proceedings of the European Conference on Computer Vision (ECCV), 268-285, 2020
1102020
Multi-Task Learning for Dense Prediction Tasks: A Survey
S Vandenhende, S Georgoulis, W Van Gansbeke, M Proesmans, D Dai, ...
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021
90*2021
End-to-end lane detection through differentiable least-squares fitting
W Van Gansbeke, B De Brabandere, D Neven, M Proesmans, L Van Gool
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
60*2019
Don't Forget The Past: Recurrent Depth Estimation from Monocular Video
V Patil, W Van Gansbeke, D Dai, L Van Gool
IEEE Robotics and Automation Letters 5 (4), 6813-6820, 2020
402020
Unsupervised semantic segmentation by contrasting object mask proposals
W Van Gansbeke, S Vandenhende, S Georgoulis, L Van Gool
Proceedings of the International Conference on Computer Vision (ICCV), 10052 …, 2021
322021
Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations
W Van Gansbeke, S Vandenhende, S Georgoulis, L Van Gool
Proceedings of the Advances in Neural Information Processing Systems (NeurIPS), 2021
12021
Computer-implemented training method, classification method and system and computer-readable recording medium
W Abbeloos, G Othmezouri, W Van Gansbeke, S Vandenhende, ...
US Patent App. 17/327,030, 2021
2021
Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations: Supplementary Materials
W Van Gansbeke, S Vandenhende, S Georgoulis, L Van Gool
Unsupervised Semantic Segmentation by Contrasting Object Mask Proposals: Supplementary Materials
W Van Gansbeke, S Vandenhende, S Georgoulis, L Van Gool
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