Generative adversarial networks for extreme learned image compression E Agustsson, M Tschannen, F Mentzer, R Timofte, LV Gool Proceedings of the IEEE/CVF International Conference on Computer Vision, 221-231, 2019 | 641 | 2019 |
Soft-to-hard vector quantization for end-to-end learning compressible representations E Agustsson, F Mentzer, M Tschannen, L Cavigelli, R Timofte, L Benini, ... Advances in neural information processing systems 30, 2017 | 591 | 2017 |
Conditional probability models for deep image compression F Mentzer, E Agustsson, M Tschannen, R Timofte, L Van Gool Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 551 | 2018 |
High-fidelity generative image compression F Mentzer, GD Toderici, M Tschannen, E Agustsson Advances in Neural Information Processing Systems 33, 11913-11924, 2020 | 433 | 2020 |
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context M Reid, N Savinov, D Teplyashin, D Lepikhin, T Lillicrap, J Alayrac, ... arXiv preprint arXiv:2403.05530, 2024 | 358 | 2024 |
Learning for video compression with hierarchical quality and recurrent enhancement R Yang, F Mentzer, LV Gool, R Timofte Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 230 | 2020 |
Practical full resolution learned lossless image compression F Mentzer, E Agustsson, M Tschannen, R Timofte, LV Gool Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 223 | 2019 |
Towards image understanding from deep compression without decoding R Torfason, F Mentzer, E Agustsson, M Tschannen, R Timofte, L Van Gool arXiv preprint arXiv:1803.06131, 2018 | 178 | 2018 |
Learning for video compression with recurrent auto-encoder and recurrent probability model R Yang, F Mentzer, L Van Gool, R Timofte IEEE Journal of Selected Topics in Signal Processing 15 (2), 388-401, 2020 | 140 | 2020 |
Learning better lossless compression using lossy compression F Mentzer, LV Gool, M Tschannen Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 94 | 2020 |
VCT: A video compression transformer F Mentzer, G Toderici, D Minnen, SJ Hwang, S Caelles, M Lucic, ... NeurIPS '22, 2022 | 91 | 2022 |
Lossy compression with gaussian diffusion L Theis, T Salimans, MD Hoffman, F Mentzer arXiv preprint arXiv:2206.08889, 2022 | 57 | 2022 |
Finite scalar quantization: Vq-vae made simple F Mentzer, D Minnen, E Agustsson, M Tschannen arXiv preprint arXiv:2309.15505, 2023 | 51 | 2023 |
Workshop and challenge on learned image compression (clic2020) G Toderici, W Shi, R Timofte, L Theis, J Balle, E Agustsson, N Johnston, ... CVPR, 2020 | 49 | 2020 |
Neural video compression using gans for detail synthesis and propagation F Mentzer, E Agustsson, J Ballé, D Minnen, N Johnston, G Toderici European Conference on Computer Vision, 562-578, 2022 | 47* | 2022 |
Multi-realism image compression with a conditional generator E Agustsson, D Minnen, G Toderici, F Mentzer Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 42 | 2023 |
High-fidelity image compression with score-based generative models E Hoogeboom, E Agustsson, F Mentzer, L Versari, G Toderici, L Theis arXiv preprint arXiv:2305.18231, 2023 | 19 | 2023 |
Deep structured features for semantic segmentation M Tschannen, L Cavigelli, F Mentzer, T Wiatowski, L Benini 2017 25th European Signal Processing Conference (EUSIPCO), 61-65, 2017 | 16 | 2017 |
M2t: Masking transformers twice for faster decoding F Mentzer, E Agustson, M Tschannen Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 8 | 2023 |
Givt: Generative infinite-vocabulary transformers M Tschannen, C Eastwood, F Mentzer arXiv preprint arXiv:2312.02116, 2023 | 5 | 2023 |