Showing 50 publications by Iro Laina
Rethinking Image Super-Resolution from Training Data Perspectives
Ohtani G, Tadokoro R, Yamada R, Asano YM, Laina I et al. (2025), 15075, 19-36
Scaling Backwards: Minimal Synthetic Pre-Training?
Nakamura R, Tadokoro R, Yamada R, Asano YM, Laina I et al. (2025), 15073, 153-171
N2F2: hierarchical scene understanding with nested neural feature fields
Bhalgat Y, Laina I, Henriques J, Zisserman A & Vedaldi A (2024), Computer Vision – ECCV 2024 18th European Conference, Milan, Italy, September 29–October 4, 2024, Proceedings, Part LIX, 197-214
Contrastive lift: 3D object instance segmentation by slow-fast contrastive fusion
Bhalgat Y, Laina I, Henriques J, Zisserman A & Vedaldi A (2024), Advances in Neural Information Processing Systems 36, 9092
BibTeX
@inproceedings{contrastivelift-2024/10,
title={Contrastive lift: 3D object instance segmentation by slow-fast contrastive fusion},
author={Bhalgat Y, Laina I, Henriques J, Zisserman A & Vedaldi A},
booktitle={37th Conference in Neural Information Processing Systems (NeurIPS 2023)},
pages={9092},
year = "2024"
}
Diffusion models for open-vocabulary segmentation
Karazija L, Laina I, Vedaldi A & Rupprecht C (2024), Computer Vision – ECCV 2024: 18th European Conference, Milan, Italy, September 29–October 4, 2024, Proceedings, Part V, 299-317
Splatt3R: Zero-shot Gaussian Splatting from Uncalibrated Image Pairs
Smart B, Zheng C, Laina I & Prisacariu VA (2024)
3D-aware instance segmentation and tracking in egocentric videos
Bhalgat Y, Tschernezki V, Laina I, Henriques J, Vedaldi A et al. (2024)
SHAP-EDITOR: instruction-guided latent 3D editing in seconds
Chen M, Xie J, Laina I & Vedaldi A (2024), 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 26446-26456
When LLMs step into the 3D World: A Survey and Meta-Analysis of 3D Tasks via Multi-modal Large Language Models
Ma X, Bhalgat Y, Smart B, Chen S, Li X et al. (2024)
Training-free layout control with cross-attention guidance
Chen M, Laina I & Vedaldi A (2024), 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 5331-5341
Invisible stitch: generating smooth 3D scenes with depth inpainting
Engstler P, Vedaldi A, Laina I & Rupprecht C (2024)
N2F2: Hierarchical Scene Understanding with Nested Neural Feature Fields
Bhalgat Y, Laina I, Henriques JF, Zisserman A & Vedaldi A (2024)
IM-3D: iterative multiview diffusion and reconstruction for high-quality 3D generation
Melas-Kyriazi L, Laina I, Rupprecht C, Neverova N, Vedaldi A et al. (2024)
EPIC Fields: marrying 3D geometry and video understanding
Tschernezki V, Darkhalil A, Zhu Z, Fouhey D, Laina I et al. (2024), Proceedings of Advances in Neural Information Processing Systems (NeurIPS): Track on Datasets and Benchmarks, 2023, 36, 26485-26500
BibTeX
@inproceedings{epicfieldsmarry-2024/1,
title={EPIC Fields: marrying 3D geometry and video understanding},
author={Tschernezki V, Darkhalil A, Zhu Z, Fouhey D, Laina I et al.},
booktitle={Advances in Neural Information Processing Systems (NeurIPS2023)},
pages={26485-26500},
year = "2024"
}
RealFusion: 360 reconstruction of any object from a single image
Melas-Kyriazi L, Laina I, Rupprecht C & Vedaldi A (2023), 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 8446-8455
Contrastive Lift: 3D Object Instance Segmentation by Slow-Fast Contrastive Fusion
Bhalgat Y, Laina I, Henriques JF, Zisserman A & Vedaldi A (2023)
EPIC Fields: marrying 3D geometry and video understanding
Tschernezki V, Darkhalil A, Zhu Z, Fouhey D, Laina I et al. (2023)
Neural feature fusion fields: 3D distillation of self-supervised 2D image representations
Tschernezki V, Laina I, Larlus D & Vedaldi A (2023), 2022 International Conference on 3D Vision (3DV), 443-453
RealFusion: 360° reconstruction of any object from a single image
Melas-Kyriazi L, Rupprecht C, Laina I & Vedaldi A (2023)
Guess what moves: unsupervised video and image segmentation by anticipating motion
Choudhury S, Karazija L, Laina I, Vedaldi A & Rupprecht C (2022), 33rd British Machine Vision Conference Proceedings
BibTeX
@inproceedings{guesswhatmovesu-2022/11,
title={Guess what moves: unsupervised video and image segmentation by anticipating motion},
author={Choudhury S, Karazija L, Laina I, Vedaldi A & Rupprecht C},
booktitle={33rd British Machine Vision Conference (BMVC 2022)},
year = "2022"
}
Unsupervised multi-object segmentation by predicting probable motion patterns
Karazija L, Choudhury S, Laina I, Rupprecht C & Vedaldi A (2022)
Deep spectral methods: a surprisingly strong baseline for unsupervised semantic segmentation and localization
Melas-Kyriazi L, Rupprecht C, Laina I & Vedaldi A (2022), 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 8354-8365
BibTeX
@inproceedings{deepspectralmet-2022/9,
title={Deep spectral methods: a surprisingly strong baseline for unsupervised semantic segmentation and localization},
author={Melas-Kyriazi L, Rupprecht C, Laina I & Vedaldi A},
booktitle={IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR 2022)},
pages={8354-8365},
year = "2022"
}
Neural feature fusion fields: 3D distillation of self-supervised 2D image representations
Tschernezki V, Laina I, Larlus D & Vedaldi A (2022)
Measuring the interpretability of unsupervised representations via quantized reverse probing
Laina I, Asano YM & Vedaldi A (2022)
Guess what moves: unsupervised video and image segmentation by anticipating motion
Choudhury S, Karazija L, Laina I, Vedaldi A & Rupprecht C (2022)
Deep spectral methods: a surprisingly strong baseline for unsupervised semantic segmentation and localization
Melas-Kyriazi L, Rupprecht C, Laina I & Vedaldi A (2022)
The curious layperson: fine-grained image recognition without expert labels
Choudhury S, Laina I, Rupprecht C & Vedaldi A (2022), Proceedings of the 32nd British Machine Vision Conference (BMVC 2021)
BibTeX
@inproceedings{thecuriouslaype-2022/3,
title={The curious layperson: fine-grained image recognition without expert labels},
author={Choudhury S, Laina I, Rupprecht C & Vedaldi A},
booktitle={32nd British Machine Vision Conference (BMVC 2021)},
year = "2022"
}
Unsupervised multi-object segmentation by predicting probable motion patterns
Karazija L, Choudhury S, Laina I, Rupprecht C & Vedaldi A (2022), Advances in Neural Information Processing Systems 35 (NeurIPS 2022), 35
BibTeX
@inproceedings{unsupervisedmul-2022/1,
title={Unsupervised multi-object segmentation by predicting probable motion patterns},
author={Karazija L, Choudhury S, Laina I, Rupprecht C & Vedaldi A},
booktitle={36th Neural Information Processing Systems (NeurIPS 2022)},
year = "2022"
}
Unsupervised part discovery from contrastive reconstruction
Choudhury S, Laina I, Rupprecht C & Vedaldi A (2021), Proceedings of the 34th Conference on Neural Information Processing Systems (NeuRIPS 2021)
BibTeX
@inproceedings{unsupervisedpar-2021/12,
title={Unsupervised part discovery from contrastive reconstruction},
author={Choudhury S, Laina I, Rupprecht C & Vedaldi A},
booktitle={34th Conference on Neural Information Processing Systems (NeuRIPS 2021)},
year = "2021"
}
The curious layperson: fine-grained image recognition without expert labels
Choudhury S, Laina I, Rupprecht C & Vedaldi A (2021)
Measuring the interpretability of unsupervised representations via quantized reversed probing
Laina I, Asano Y & Vedaldi A (2021), International Conference on Learning Representations
BibTeX
@inproceedings{measuringtheint-2021/9,
title={Measuring the interpretability of unsupervised representations via quantized reversed probing},
author={Laina I, Asano Y & Vedaldi A},
booktitle={Tenth International Conference on Learning Representations (ICLR 2022)},
year = "2021"
}
Finding an unsupervised image segmenter in each of your deep generative models
Melas-Kyriazi L, Rupprecht C, Laina I & Vedaldi A (2021), International Conference on Learning Representations
BibTeX
@inproceedings{findinganunsupe-2021/9,
title={Finding an unsupervised image segmenter in each of your deep generative models},
author={Melas-Kyriazi L, Rupprecht C, Laina I & Vedaldi A},
booktitle={ Tenth International Conference on Learning Representations (ICLR 2022)},
year = "2021"
}
Quantifying learnability and describability of visual concepts emerging in representation learning
Laina I, Fong RC & Vedaldi A (2021), Advances in Neural Information Processing Systems 33, 16, 13112-13126
BibTeX
@inproceedings{quantifyinglear-2021/7,
title={Quantifying learnability and describability of visual concepts emerging in representation learning},
author={Laina I, Fong RC & Vedaldi A},
booktitle={34th Annual Conference on Neural Information Processing Systems (NeurIPS 2020)},
pages={13112-13126},
year = "2021"
}
Finding an unsupervised image segmenter in each of your deep generative models
Melas-Kyriazi L, Rupprecht C, Laina I & Vedaldi A (2021)
The Curious Layperson: Fine-Grained Image Recognition without Expert Labels
Choudhury S, Laina I, Rupprecht C & Vedaldi A (2021), 32nd British Machine Vision Conference, BMVC 2021
BibTeX
@inproceedings{thecuriouslaype-2021/1,
title={The Curious Layperson: Fine-Grained Image Recognition without Expert Labels},
author={Choudhury S, Laina I, Rupprecht C & Vedaldi A},
year = "2021"
}
Quantifying learnability and describability of visual concepts emerging in representation learning
Laina I, Fong RC & Vedaldi A (2020)
Semantic Image Manipulation Using Scene Graphs
Dhamo H, Farshad A, Laina I, Navab N, Hager GD et al. (2020), 00, 5212-5221
Towards Unsupervised Image Captioning with Shared Multimodal Embeddings
Laina I, Rupprecht C & Navab N (2019), 00, 7413-7423
Dealing with Ambiguity in Robotic Grasping via Multiple Predictions
Ghazaei G, Laina I, Rupprecht C, Tombari F, Navab N et al. (2019), Lecture Notes in Computer Science, 11364, 38-55
Guide Me: Interacting with Deep Networks
Rupprecht C, Laina I, Navab N, Hager GD & Tombari F (2018), 8551-8561
Learning in an Uncertain World: Representing Ambiguity Through Multiple Hypotheses
Rupprecht C, Laina I, DiPietro R, Baust M, Tombari F et al. (2017), 3611-3620
BibTeX
@inproceedings{learninginanunc-2017/10,
title={Learning in an Uncertain World: Representing Ambiguity Through Multiple Hypotheses},
author={Rupprecht C, Laina I, DiPietro R, Baust M, Tombari F et al.},
booktitle={2017 IEEE International Conference on Computer Vision (ICCV)},
pages={3611-3620},
year = "2017"
}
Concurrent Segmentation and Localization for Tracking of Surgical Instruments
Laina I, Rieke N, Rupprecht C, Vizcaíno JP, Eslami A et al. (2017), Lecture Notes in Computer Science, 10434, 664-672
Deeper Depth Prediction with Fully Convolutional Residual Networks
Laina I, Rupprecht C, Belagiannis V, Tombari F & Navab N (2016)
Deeper Depth Prediction with Fully Convolutional Residual Networks
Laina I, Rupprecht C, Belagiannis V, Tombari F & Navab N (0), 239-248
RealFusion: 360 Reconstruction of Any Object from a Single Image
Melas-Kyriazi L, Laina I, Rupprecht C & Vedaldi A (0)
BibTeX
@inproceedings{realfusionrecon-/,
title={RealFusion: 360 Reconstruction of Any Object from a Single Image},
author={Melas-Kyriazi L, Laina I, Rupprecht C & Vedaldi A},
booktitle={Conference on Computer Vision and Pattern Recognition (CVPR), 2023}
}