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Martin Danelljan
Biography
I am senior computer vision research engineer at the 3D Vision group at Apple, where I am building a team working on 3D computer vision at a global scale. Previously, I was a research group leader at ETH Zurich and founder of Elevate3D. I received my Ph.D. degree from Linköping University, Sweden in 2018. My thesis “Visual Tracking” was awarded the biennial Best Nordic Thesis Prize.
Hiring: I am looking for very talented researchers and engineers in computer vision and machine learning to join our group at Apple. Contact me if you are interested!
News:
- Joined Apple in Nov. 2023.
- Three NeurIPS 2023 papers accepted.
- Three ICCV 2023 papers accepted.
Selected Publications
NeurIPS 2023
Extending Segment Anything (SAM) to achieve pixel-accurate segmentations of any object.
Extending Segment Anything (SAM) to achieve pixel-accurate segmentations of any object.
Lei Ke,
Mingqiao Ye,
Martin Danelljan,
Yifan Liu,
Yu-Wing Tai,
Chi-Keung Tang
NeurIPS 2023
A binary network for highly efficient video matting.
A binary network for highly efficient video matting.
Haotong Qin,
Lei Ke,
Xudong Ma,
Martin Danelljan,
Yu-Wing Tai,
Chi-Keung Tang,
Xianglong Liu
NeurIPS 2023
Quantization method and architecture for super-resolution.
Quantization method and architecture for super-resolution.
Haotong Qin,
Yulun Zhang,
Yifu Ding,
Yifan Liu,
Xianglong Liu,
Martin Danelljan
ICCV 2023
Cascade attention and IoU-based scoring for object detection.
Cascade attention and IoU-based scoring for object detection.
Mingqiao Ye,
Lei Ke,
Siyuan Li,
Yu-Wing Tai,
Chi-Keung Tang,
Martin Danelljan
ICCV 2023
A method for 3d reconstruction of dynamic scenes with multi-camera setups.
A method for 3d reconstruction of dynamic scenes with multi-camera setups.
Aron Schmied,
Tobias Fischer,
Martin Danelljan,
Marc Pollefeys
ICCV 2023
A graph-based method for chemical structure recognition in documents.
A graph-based method for chemical structure recognition in documents.
Lucas Morin,
Martin Danelljan,
Maria Isabel Agea,
Ahmed Nassar,
Valery Weber,
Ingmar Meijer,
Peter Staar
CVPR 2023
State-of-the-art Video Instance Segmentation without any ground-truth masks for training.
State-of-the-art Video Instance Segmentation without any ground-truth masks for training.
Lei Ke,
Martin Danelljan,
Henghui Ding,
Yu-Wing Tai,
Chi-Keung Tang
CVPR 2023
First method and benchmark for open vocabulary tracking.
First method and benchmark for open vocabulary tracking.
Siyuan Li,
Tobias Fischer,
Lei Ke,
Henghui Ding,
Martin Danelljan
CVPR 2023
Leveraging implicit models to estimate the output confidence for unsupervised domain adaptation.
Leveraging implicit models to estimate the output confidence for unsupervised domain adaptation.
Rui Gong,
Qin Wang,
Martin Danelljan,
Dengxin Dai,
Luc Van Gool
TPAMI 2023
A method that gives you accurate dense optical flow and correspondences with robust uncertainty.
A method that gives you accurate dense optical flow and correspondences with robust uncertainty.
Prune Truong,
Martin Danelljan,
Luc Van Gool,
Radu Timofte
TPAMI 2023
Comprehensive survey over Visual Object Tracking.
Comprehensive survey over Visual Object Tracking.
Sajid Javed,
Martin Danelljan,
Fahad Shahbaz Khan,
Muhammad Haris Khan,
Michael Felsberg,
Jiri Matas
ECCV 2022
A few-shot learner based on Gaussian Processes for few-shot semantic segmentation.
A few-shot learner based on Gaussian Processes for few-shot semantic segmentation.
Joakim Johnander,
Johan Edstedt,
Michael Felsberg,
Fahad Shahbaz Khan,
Martin Danelljan
ECCV 2022
Bringing the robustness in tracking to video segmentation.
Bringing the robustness in tracking to video segmentation.
Matthieu Paul,
Martin Danelljan,
Christoph Mayer,
Luc Van Gool
ECCV 2022
A method and dataset for learning the camera ISP in the wild.
A method and dataset for learning the camera ISP in the wild.
Ardhendu Tripathi,
Martin Danelljan,
Samarth Shukla,
Radu Timofte,
Luc Van Gool
ECCV 2022
A new method and metric for large-scale and open world multi-object tracking.
A new method and metric for large-scale and open world multi-object tracking.
Siyuan Li,
Martin Danelljan,
Henghui Ding,
Thomas Huang
ECCV 2022
An efficient transformer-based method for highly accurate video instance segmentation.
An efficient transformer-based method for highly accurate video instance segmentation.
Lei Ke,
Henghui Ding,
Martin Danelljan,
Yu-Wing Tai,
Chi-Keung Tang
ECCV 2022
Bringing the robustness in tracking to video segmentation.
Bringing the robustness in tracking to video segmentation.
Rui Gong,
Martin Danelljan,
Dengxin Dai,
Danda Pani Paudel,
Ajad Chhatkuli,
Luc Van Gool
CVPR 2022
A Probabilistic Denoising Diffusion Model for image inpainting.
A Probabilistic Denoising Diffusion Model for image inpainting.
Andreas Lugmayr,
Martin Danelljan,
Andres Romero,
Radu Timofte,
Luc Van Gool
CVPR 2022
An efficient transformer-based method for highly accurate instance segmentation.
An efficient transformer-based method for highly accurate instance segmentation.
Lei Ke,
Martin Danelljan,
Xia Li,
Yu-Wing Tai,
Chi-Keung Tang
CVPR 2022
A weakly-supervised method for learning dense semantic correspondences.
A weakly-supervised method for learning dense semantic correspondences.
Prune Truong,
Martin Danelljan,
Luc Van Gool
CVPR 2022
A Multi-Object Tracking algorithm that can be solved with Adiabatic Quantum Computing
A Multi-Object Tracking algorithm that can be solved with Adiabatic Quantum Computing
Jan-Nico Zäch,
Alexander Liniger,
Martin Danelljan,
Dengxin Dai,
Luc Van Gool
CVPR 2022
A transformer-based tracker inspired by discriminative correlation filters.
A transformer-based tracker inspired by discriminative correlation filters.
Christoph Mayer,
Martin Danelljan,
Goutam Bhat,
Matthieu Paul,
Danda Pani Paudel,
Luc Van Gool
CVPR 2022
A GAN that generates consistent images at arbitrary scales and resolutions.
A GAN that generates consistent images at arbitrary scales and resolutions.
Evangelos Ntavelis,
Mohamad Shahbazi,
Iason Kastanis,
Radu Timofte,
Martin Danelljan,
Luc Van Gool
ICLR 2022
Analyzing and addressing mode collapse in conditional GANs caused by the conditioning itself.
Analyzing and addressing mode collapse in conditional GANs caused by the conditioning itself.
Mohamad Shahbazi,
Martin Danelljan,
Danda Pani Paudel,
Luc Van Gool
ICRA 2022
An online 3D Multi-Object Tracking method based on graph neural networks.
An online 3D Multi-Object Tracking method based on graph neural networks.
Jan-Nico Zäch,
Dengxin Dai,
Alexander Liniger,
Martin Danelljan,
Luc Van Gool
NeurIPS 2021 Spotlight
Efficient cross-attention for video instance segmentation.
Efficient cross-attention for video instance segmentation.
Lei Ke,
Xia Li,
Martin Danelljan,
Yu-Wing Tai,
Chi-Keung Tang
ICCV 2021 Oral
Unsupervised method for learning dense correspondences and optical flow on real image pairs.
Unsupervised method for learning dense correspondences and optical flow on real image pairs.
Prune Truong,
Martin Danelljan,
Luc Van Gool
ICCV 2021 Oral
Deep optimization-based formulation for multi-frame super-resolution and denoising.
Deep optimization-based formulation for multi-frame super-resolution and denoising.
Goutam Bhat,
Martin Danelljan,
Luc Van Gool,
Radu Timofte
ICCV 2021
An optimization-based architecture for converting video bounding box annotations to segmentation masks.
An optimization-based architecture for converting video bounding box annotations to segmentation masks.
Bin Zhao,
Goutam Bhat,
Martin Danelljan,
Luc Van Gool,
Radu Timofte
ICCV 2021
Associating the target and distractor objects for robust visual tracking.
Associating the target and distractor objects for robust visual tracking.
Christoph Mayer,
Martin Danelljan,
Danda Pani Paudel,
Luc Van Gool
ICCV 2021
A unified hierarchical normalizing flow architecture for super-resolution and image rescaling.
A unified hierarchical normalizing flow architecture for super-resolution and image rescaling.
Jingyun Liang,
Andreas Lugmayr,
Kai Zhang,
Martin Danelljan,
Luc Van Gool,
Radu Timofte
ICCV 2021
Reducing memory complexity for training semantic segmentation models with large number of classes.
Reducing memory complexity for training semantic segmentation models with large number of classes.
Shipra Jain,
Danda Pani Paudel,
Martin Danelljan,
Luc Van Gool
IROS 2021
A local memory cross-attention module for fast video semantic segmentation.
A local memory cross-attention module for fast video semantic segmentation.
Matthieu Paul,
Martin Danelljan,
Luc Van Gool,
Radu Timofte
CVPR 2021 Oral
A method that gives you accurate dense optical flow and correspondences with robust uncertainty.
A method that gives you accurate dense optical flow and correspondences with robust uncertainty.
Prune Truong,
Martin Danelljan,
Luc Van Gool,
Radu Timofte
CVPR 2021 Oral
A novel unpaired learning formulation for conditional normalizing flows with applications to learning image degradations.
A novel unpaired learning formulation for conditional normalizing flows with applications to learning image degradations.
Valentin Wolf,
Andreas Lugmayr,
Martin Danelljan,
Luc Van Gool,
Radu Timofte
CVPR 2021
An attention based architecture and real-world dataset for burst super-resolution.
An attention based architecture and real-world dataset for burst super-resolution.
Goutam Bhat,
Martin Danelljan,
Luc Van Gool,
Radu Timofte
CVPR 2021
We tackle the problem of convolutional neural network design by adjusting the channel configurations of predefined networks.
We tackle the problem of convolutional neural network design by adjusting the channel configurations of predefined networks.
Yawei Li,
Wen Li,
Martin Danelljan,
Kai Zhang,
Shuhang Gu,
Luc Van Gool,
Radu Timofte
ICRA 2021
An optimization-based meta-learning approach for few-shot classification.
An optimization-based meta-learning approach for few-shot classification.
Ardhendu Tripathi,
Martin Danelljan,
Luc Van Gool,
Radu Timofte
NeurIPS 2020
Dataset and method for generating vector graphics.
Dataset and method for generating vector graphics.
Alexandre Carlier,
Martin Danelljan,
Alexandre Alahi,
Radu Timofte
NeurIPS 2020
A fully differentiable dense matching module for your correspondence or optical flow network.
A fully differentiable dense matching module for your correspondence or optical flow network.
Prune Truong,
Martin Danelljan,
Luc Van Gool,
Radu Timofte
BMVC 2020
Investigating how to train a deep energy-based model for accurate regression.
Investigating how to train a deep energy-based model for accurate regression.
Fredrik Gustafsson,
Martin Danelljan,
Radu Timofte,
Thomas Schön
ECCV 2020 Oral
An optimization-based few-shot learner for VOS.
An optimization-based few-shot learner for VOS.
Goutam Bhat,
Felix Järemo Lawin,
Martin Danelljan,
Andreas Robinson,
Michael Felsberg,
Luc Van Gool,
Radu Timofte
ECCV 2020 Spotlight
Normalizing flow based super-resolution method capable of learning the conditional distribution of the output given the low-resolution input.
Normalizing flow based super-resolution method capable of learning the conditional distribution of the output given the low-resolution input.
Andreas Lugmayr,
Martin Danelljan,
Luc Van Gool,
Radu Timofte
ECCV 2020
A general method for accurate regression by learning the conditional target probability distribution as a deep energy-based model.
A general method for accurate regression by learning the conditional target probability distribution as a deep energy-based model.
Fredrik Gustafsson,
Martin Danelljan,
Goutam Bhat,
Thomas Schön
ECCV 2020 Spotlight
A graph-based memory module for Video Object Segmentation.
A graph-based memory module for Video Object Segmentation.
Xinkai Lu,
Wenguan Wang,
Martin Danelljan,
Tianfei Zhou,
Jianbing Shen,
Luc Van Gool
ECCV 2020
A tracking architecture that exploits the knowledge about the presence of other objects in the surrounding scene to prevent failure.
A tracking architecture that exploits the knowledge about the presence of other objects in the surrounding scene to prevent failure.
Goutam Bhat,
Martin Danelljan,
Luc Van Gool,
Radu Timofte
CVPR 2020 Oral
A unified network architecture for dense correspondences applicable to geometric matching, optical flow and semantic matching.
A unified network architecture for dense correspondences applicable to geometric matching, optical flow and semantic matching.
Prune Truong,
Martin Danelljan,
Radu Timofte
CVPR 2020 Oral
A light-weight optimization-based target model for fast VOS.
A light-weight optimization-based target model for fast VOS.
Andreas Robinson,
Felix Järemo Lawin,
Martin Danelljan,
Fahad Shahbaz Khan,
Michael Felsberg
CVPR 2020
Proposes a general formulation for probabilistic regression, which is then applied to visual tracking.
Proposes a general formulation for probabilistic regression, which is then applied to visual tracking.
Martin Danelljan,
Luc Van Gool,
Radu Timofte
CVPR 2020
A fully-convolutional approach that directly detects the interactions between human-object pairs.
A fully-convolutional approach that directly detects the interactions between human-object pairs.
Tiancai Wang,
Tong Yang,
Martin Danelljan,
Fahad Shahbaz Khan,
Xiangyu Zhang,
Jian Sun
ICCV 2019 Oral
An end-to-end tracking architecture, capable of fully exploiting both target and background appearance information for target model prediction.
An end-to-end tracking architecture, capable of fully exploiting both target and background appearance information for target model prediction.
Goutam Bhat,
Martin Danelljan,
Luc Van Gool,
Radu Timofte
ICCV 2019
Replacing the handcrafted update function in Siamese trackers with a learnable update mechanism.
Replacing the handcrafted update function in Siamese trackers with a learnable update mechanism.
Lichao Zhang,
Abel Gonzalez-Garcia,
Joost van de Weijer,
Martin Danelljan,
Fahad Shahbaz Khan
BMVC 2019
“e propose a tracking framework that can exploit semantic information, without sacrificing the generic nature of the tracker.
“e propose a tracking framework that can exploit semantic information, without sacrificing the generic nature of the tracker.
Ardhendu Tripathi,
Martin Danelljan,
Luc Van Gool,
Radu Timofte
CVPR 2019 Oral
Performing accurate bounding box estimation for generic visual tracking.
Performing accurate bounding box estimation for generic visual tracking.
Martin Danelljan,
Goutam Bhat,
Fahad Shahbaz Khan,
Michael Felsberg
CVPR 2019 Oral
A generative appearance module for end-to-end VOS.
A generative appearance module for end-to-end VOS.
Joakim Johnander,
Martin Danelljan,
Emil Brissman,
Fahad Shahbaz Khan,
Michael Felsberg
ECCV 2019
How to better utilize deep features for correlation-based tracking.
How to better utilize deep features for correlation-based tracking.
Goutam Bhat,
Joakim Johnander,
Martin Danelljan,
Fahad Shahbaz Khan,
Michael Felsberg
CVPR 2018 Oral
Revisiting the foundations of probabilistic point cloud registration in order to tackle the key issue of sampling density variations.
Revisiting the foundations of probabilistic point cloud registration in order to tackle the key issue of sampling density variations.
Felix Järemo Lawin,
Martin Danelljan,
Fahad Shahbaz Khan,
Per-Erik Forssén,
Michael Felsberg
CVPR 2017
Tackling the key causes behind the problems of computational complexity and over-fitting in correlation trackers.
Tackling the key causes behind the problems of computational complexity and over-fitting in correlation trackers.
Martin Danelljan,
Goutam Bhat,
Fahad Shahbaz Khan,
Michael Felsberg
ECCV 2016 Oral
A theoretical framework for discriminatively learning a convolution operator in the continuous spatial domain.
A theoretical framework for discriminatively learning a convolution operator in the continuous spatial domain.
Martin Danelljan,
Andreas Robinson,
Fahad Shahbaz Khan,
Michael Felsberg
CVPR 2016
A probabilistic point set registration framework that exploits available color information associated with the points.
A probabilistic point set registration framework that exploits available color information associated with the points.
Martin Danelljan,
Giulia Meneghetti,
Fahad Shahbaz Khan,
Michael Felsberg
CVPR 2016
A unified formulation for alleviating the problem of corrupted training samples in tracking-by-detection methods.
A unified formulation for alleviating the problem of corrupted training samples in tracking-by-detection methods.
Martin Danelljan,
Gustav Häger,
Fahad Shahbaz Khan,
Michael Felsberg
ICCV 2015
Mitigating the unwanted boundary effects, which limits the performance of correlation based trackers.
Mitigating the unwanted boundary effects, which limits the performance of correlation based trackers.
Martin Danelljan,
Gustav Häger,
Fahad Shahbaz Khan,
Michael Felsberg
TPAMI & BMVC 2014
Accurate and fast scale estimation for visual tracking.
Accurate and fast scale estimation for visual tracking.
Martin Danelljan,
Gustav Häger,
Fahad Shahbaz Khan,
Michael Felsberg
CVPR 2014 Oral
How to incorporate color information into visual tracking.
How to incorporate color information into visual tracking.
Martin Danelljan,
Fahad Shahbaz Khan,
Michael Felsberg,
Joost van de Weijer
Graduated PhD Students
Contact
- martin.danelljan [at] gmail.com
- Mountain View, California