Aravindh Mahendran
Aravindh Mahendran
Google Research, Brain Team
Zweryfikowany adres z google.com - Strona główna
Cytowane przez
Cytowane przez
Understanding deep image representations by inverting them
A Mahendran, A Vedaldi
Proceedings of the IEEE conference on computer vision and pattern …, 2015
Visualizing deep convolutional neural networks using natural pre-images
A Mahendran, A Vedaldi
International Journal of Computer Vision 120, 233-255, 2016
Object-centric learning with slot attention
F Locatello, D Weissenborn, T Unterthiner, A Mahendran, G Heigold, ...
Advances in Neural Information Processing Systems 33, 11525-11538, 2020
Salient deconvolutional networks
A Mahendran, A Vedaldi
Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016
Cross pixel optical-flow similarity for self-supervised learning
A Mahendran, J Thewlis, A Vedaldi
Computer Vision–ACCV 2018: 14th Asian Conference on Computer Vision, Perth …, 2019
Conditional object-centric learning from video
T Kipf, GF Elsayed, A Mahendran, A Stone, S Sabour, G Heigold, ...
arXiv preprint arXiv:2111.12594, 2021
Self-supervised learning of video-induced visual invariances
M Tschannen, J Djolonga, M Ritter, A Mahendran, N Houlsby, S Gelly, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
Differentiable patch selection for image recognition
JB Cordonnier, A Mahendran, A Dosovitskiy, D Weissenborn, J Uszkoreit, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
Heterogeneous UGV-MAV exploration using integer programming
A Dewan, A Mahendran, N Soni, KM Krishna
Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International …, 2013
Simple open-vocabulary object detection with vision transformers
M Minderer, A Gritsenko, A Stone, M Neumann, D Weissenborn, ...
arXiv preprint arXiv:2205.06230, 2022
Researchdoom and cocodoom: Learning computer vision with games
A Mahendran, H Bilen, JF Henriques, A Vedaldi
arXiv preprint arXiv:1610.02431, 2016
Savi++: Towards end-to-end object-centric learning from real-world videos
GF Elsayed, A Mahendran, S van Steenkiste, K Greff, MC Mozer, T Kipf
arXiv preprint arXiv:2206.07764, 2022
Object scene representation transformer
MSM Sajjadi, D Duckworth, A Mahendran, S van Steenkiste, F Pavetić, ...
arXiv preprint arXiv:2206.06922, 2022
Self-supervised segmentation by grouping optical-flow
A Mahendran, J Thewlis, A Vedaldi
Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 0-0, 2018
Representation learning from videos in-the-wild: An object-centric approach
R Romijnders, A Mahendran, M Tschannen, J Djolonga, M Ritter, ...
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2021
UGV-MAV collaboration for augmented 2D maps
A Mahendran, A Dewan, N Soni, KM Krishna
Proceedings of Conference on Advances In Robotics, 1-6, 2013
Bus detection for adaptive traffic signal control
A Mahendran, M Hebert, S Smith, XF Xie
Carnegie-Mellon University, 2014
Optimization Based coordinated uGV-MAV exploration for 2D augmented mapping
A Dewan, A Mahendran, N Soni, KM Krishna
Proceedings of the 2013 international conference on Autonomous agents and …, 2013
Self-supervised learning using motion and visualizing convolutional neural networks
A Mahendran
University of Oxford, 2018
Exploiting domain constraints for exemplar based bus detection for traffic scheduling
A Mahendran, M Hebert, S Smith
17th International IEEE Conference on Intelligent Transportation Systems …, 2014
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