Sébastien Ehrhardt
Sébastien Ehrhardt
Verified email at robots.ox.ac.uk
Title
Cited by
Cited by
Year
Learning a physical long-term predictor
S Ehrhardt, A Monszpart, NJ Mitra, A Vedaldi
arXiv preprint arXiv:1703.00247, 2017
392017
Semi-supervised learning with scarce annotations
SA Rebuffi, S Ehrhardt, K Han, A Vedaldi, A Zisserman
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
172020
Taking visual motion prediction to new heightfields
S Ehrhardt, A Monszpart, NJ Mitra, A Vedaldi
Computer Vision and Image Understanding 181, 14-25, 2019
152019
Automatically discovering and learning new visual categories with ranking statistics
S Ehrhardt, A Zisserman, SA Rebuffi, K Han, A Vedaldi
Proceedings of the 8th Intennational Conference on Learning Representations …, 0
15*
Unsupervised intuitive physics from visual observations
S Ehrhardt, A Monszpart, N Mitra, A Vedaldi
Asian Conference on Computer Vision, 700-716, 2018
132018
Learning to represent mechanics via long-term extrapolation and interpolation
S Ehrhardt, A Monszpart, A Vedaldi, N Mitra
arXiv preprint arXiv:1706.02179, 2017
82017
RELATE: Physically Plausible Multi-Object Scene Synthesis Using Structured Latent Spaces
S Ehrhardt, O Groth, A Monszpart, M Engelcke, I Posner, N Mitra, ...
Advances in Neural Information Processing Systems 33, 2020
62020
D2D: Learning to find good correspondences for image matching and manipulation
O Wiles, S Ehrhardt, A Zisserman
arXiv preprint arXiv:2007.08480, 2020
52020
Small steps and giant leaps: Minimal newton solvers for deep learning
JF Henriques, S Ehrhardt, S Albanie, A Vedaldi
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
52019
Stopping gan violence: Generative unadversarial networks
S Albanie, S Ehrhardt, JF Henriques
arXiv preprint arXiv:1703.02528, 2017
52017
Lsd-c: Linearly separable deep clusters
SA Rebuffi, S Ehrhardt, K Han, A Vedaldi, A Zisserman
arXiv preprint arXiv:2006.10039, 2020
42020
3D Multi-bodies: Fitting Sets of Plausible 3D Human Models to Ambiguous Image Data
B Biggs, S Ehrhadt, H Joo, B Graham, A Vedaldi, D Novotny
arXiv preprint arXiv:2011.00980, 2020
12020
Unsupervised Intuitive Physics from Past Experiences
S Ehrhardt, A Monszpart, NJ Mitra, A Vedaldi
arXiv preprint arXiv:1905.10793, 2019
12019
Deep Industrial Espionage
S Albanie, J Thewlis, S Ehrhardt, J Henriques
arXiv preprint arXiv:1904.01114, 2019
12019
Co-attention for conditioned image matching
O Wiles, S Ehrhardt, A Zisserman
Institute of Electrical and Electronics Engineers, 2021
2021
Learning visual concepts with fewer human annotations
S Ehrhardt
University of Oxford, 2020
2020
Unsupervised Intuitive Physics from Visual Observations Download PDF
S Ehrhardt, A Monszpart, N Mitra, A Vedaldi
How does mini-batching affect curvature information for second order deep learning optimization?
D Granziol, X Wan, S Zohren, S Roberts, T Garipov, D Vetrov, AG Wilson, ...
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