Fatemeh's homepage

Fatemeh Saleh

Senior Research Scientist
Microsoft, Cambridge, UK

I'm a research scientist at Microsoft in Cambridge, UK. My research focus is on developing computer vision and machine learning solutions for digital humans, including the 3D reconstruction of human faces and bodies. During my Ph.D at Australian National University, I worked on computer vision and machine learning with an emphasis on human understanding, including action and motion analysis, as well as scene understanding.

Publications

Look Ma, no markers: holistic performance capture without the hassle
Charlie Hewitt, Fatemeh Saleh, Sadegh Aliakbarian, Lohit Petikam, Shideh Rezaeifar, Louis Florentin, Zafiirah Hosenie, Thomas J Cashman, Julien Valentin, Darren Cosker, Tadas Baltrusaitis
ACM Transactions on Graphics (TOG) / SIGGRAPH Asia, 2024
[project page / arXiv / Video / code]

Eyelid Fold Consistency in Facial Modeling
Lohit Petikam, Charlie Hewitt, Fatemeh Saleh, Tadas Baltrušaitis
SIGGRAPH Asia, 2024
[project page / arXiv / Video / code]

HMD-NeMo: Online 3D Avatar Motion Generation From Sparse Observations
Sadegh Aliakbarian, Fatemeh Saleh, David Collier, Pashmina Cameron, Darren Cosker
International Conference on Computer Vision (ICCV), 2023
[project page / arXiv / Video / code]

Effective Self-supervised Pre-training on Low-compute Networks without Distillation
Fuwen Tan, Fatemeh Saleh, Brais Martinez
International Conference on Learning Representations (ICLR), 2023
[project page / arXiv / video ]

JRDB-Act: A Large-scale Dataset for Spatio-temporal Action, Social Group and Activity Detection
Mahsa Ehsanpour, Fatemeh Saleh, Silvio Savarese, Ian Reid, Hamid Rezatofighi
Proceedings of the IEEE international conference on computer vision (CVPR), 2022
[project page / arXiv / video ]

Contextually Plausible and Diverse 3D Human Motion Prediction
Sadegh Aliakbarian, Fatemeh Saleh, Lars Petersson, Mathieu Salzmann, Stephen Gould
International Conference on Computer Vision (ICCV), 2021 (Oral presentation)
[project page / arXiv / video ]

Uncertainty Inspired RGB-D Saliency Detection
Jing Zhang, Deng-Ping Fan, Yuchao Dai, Saeed Anwar, Fatemeh Saleh, Sadegh Aliakbarian, Nick Barnes
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021
[project page / arXiv / video / code]

Probabilistic Tracklet Scoring and Inpainting for Multiple Object Tracking
Fatemeh Saleh, Sadegh Aliakbarian, Hamid Rezatofighi, Mathieu Salzmann, Stephen Gould
Proceedings of the IEEE international conference on computer vision (CVPR), 2021 (Oral presentation)
[project page / arXiv / video / code]

The IKEA ASM Dataset: Understanding People Assembling Furniture through Actions, Objects and Pose
Yizhak Ben-Shabat, Xin Yu, Fatemeh Saleh, Dylan Campbell, Cristian Rodriguez-Opazo, Hongdong Li, Stephen Gould
Winter Conference on Applications of Computer Vision (WACV), 2021
[project page / arXiv / Dataset / code]

Joint learning of Social Groups, Individuals Action and Sub-group Activities in Videos
Mahsa Ehsanpour, Alireza Abedin, Fatemeh Saleh, Javen Shi, Ian Reid, Hamid Rezatofighi
European Conference on Computer Vision (ECCV), 2020
[project page / arXiv / video / code]

A Stochastic Conditioning Scheme for Diverse Human Motion Prediction
Sadegh Aliakbarian, Fatemeh Saleh, Mathieu Salzmann, Lars Petersson, Stephen Gould
Proceedings of the IEEE international conference on computer vision (CVPR), 2020
[project page / arXiv / video / code]

UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders
Jing Zhang, Deng-Ping Fan, Yuchao Dai, Saeed Anwar, Fatemeh Saleh, Tong Zhang, Nick Barnes
Proceedings of the IEEE international conference on computer vision (CVPR), 2020 (Oral presentation)
[project page / arXiv / video / code]

Proposal-free Temporal Moment Localization of a Natural-Language Query in Video using Guided Attention
Cristian Rodriguez Opazo, Edison Marrese-Taylor, Fatemeh Saleh, Hongdong Li, Stephen Gould
Winter Conference on Applications of Computer Vision (WACV), 2020
[project page / arXiv / Video / Code]

Sampling Good Latent Variables via CPP-VAEs: VAEs with Condition Posterior as Prior
Sadegh Aliakbarian, Fatemeh Saleh, Mathieu Salzmann, Lars Petersson, Stephen Gould
ArXiv, 2019
[project page / arXiv / Video / Code]

VIENA2: A Driving Anticipation Dataset
Sadegh Aliakbarian, Fatemeh Saleh, Mathieu Salzmann, Basura Fernando, Lars Petersson, Lars Andersson
Asian Conference on Computer Vision (ACCV), 2018
[project page / arXiv / Video / Code]

Effective Use of Synthetic Data in Urban Scene Semantic Segmentation
Fatemeh Saleh, Sadegh Aliakbarian, Mathieu Salzmann, Lars Petersson, Jose M Alvarez
European Conference on Computer Vision (ECCV), 2018
[project page / arXiv / Video / Code]

Incorporating Network Built-in Priors in Weakly-supervised Semantic Segmentation
Fatemeh Saleh, Sadegh Aliakbarian, Mathieu Salzmann, Lars Petersson, Jose M Alvarez, Stephen Gould
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2018
[project page / arXiv / Video / Code]

Encouraging LSTMs to Anticipate Actions Very Early
Sadegh Aliakbarian, Fatemeh Saleh, Mathieu Salzmann, Basura Fernando, Lars Petersson, Lars Andersson
International Conference on Computer Vision (ICCV), 2017
[project page / arXiv / Video / Code]

Bringing background into the foreground: Making all classes equal in weakly-supervised video semantic segmentation
Fatemeh Saleh, Sadegh Aliakbarian, Mathieu Salzmann, Lars Petersson, Jose M Alvarez
International Conference on Computer Vision (ICCV), 2017
[project page / arXiv / Video / Code]

Built-in Foreground/Background Prior for Weakly-Supervised Semantic Segmentation
Fatemeh Saleh, Sadegh Aliakbarian, Mathieu Salzmann, Lars Petersson, Stephen Gould, Jose M Alvarez
European Conference on Computer Vision (ECCV), 2016
[project page / arXiv / Video / Code]

Recent Experiences

	Senior Research Scientist \| *Microsoft, Cambridge, UK* [July 2022 - Now] Developing computer vision and machine learning solutions for digital humans, including the 3D reconstruction of human faces and bodies.
	Research Scientist \| *Samsung AI Center, Cambridge, UK* [April 2021 - July 2022] Working on self-supervised representation learning.
	Research Fellow \| *Australian Centre for Robotic Vision (ACRV), Canberra, Australia* [January 2019 - March 2021] Working on analysing human motion and behaviour, e.g., multiple human tracking, diverse motion prediction, social activity analysis, and action forecasting.
	Machine Learning Research Consultant \| *Joint ACRV/LumaChain collaboration* [June 2020 - August 2020] As a research consultant, we are delivering multiple (deformable and visually similar) object tracking in highly occluded scenarios. The project is related to the real-world challenging scenarios of food chain industry.
	Research Intern \| *Qualcomm AI Research, Amsterdam, Netherlands* [May 2018 - October 2018] Working on self-supervised representation learning for video analysis tasks.