Mohammad Sadegh Ali Akbarian

According to our database, Mohammad Sadegh Ali Akbarian authored at least 16 papers between 2016 and 2020.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2020

ArTIST: Autoregressive Trajectory Inpainting and Scoring for Tracking.

Fatemeh Sadat Saleh, Mohammad Sadegh Aliakbarian, Mathieu Salzmann, Stephen Gould

CoRR, 2020

Super-resolved Chromatic Mapping of Snapshot Mosaic Image Sensors via a Texture Sensitive Residual Network.

Mehrdad Shoeiby, Lars Petersson, Mohammad Ali Armin, Mohammad Sadegh Aliakbarian, Antonio Robles-Kelly

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Mosaic Super-resolution via Sequential Feature Pyramid Networks.

Mehrdad Shoeiby, Mohammad Ali Armin, Mohammad Sadegh Aliakbarian, Saeed Anwar, Lars Petersson

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

A Stochastic Conditioning Scheme for Diverse Human Motion Prediction.

Mohammad Sadegh Aliakbarian, Fatemeh Sadat Saleh, Mathieu Salzmann, Lars Petersson, Stephen Gould

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Sampling Good Latent Variables via CPP-VAEs: VAEs with Condition Posterior as Prior.

Mohammad Sadegh Aliakbarian, Fatemeh Sadat Saleh, Mathieu Salzmann, Lars Petersson, Stephen Gould

CoRR, 2019

Multi-FAN: Multi-Spectral Mosaic Super-Resolution Via Multi-Scale Feature Aggregation Network.

Mehrdad Shoeiby, Mohammad Sadegh Aliakbarian, Saeed Anwar, Lars Petersson

CoRR, 2019

Learning Variations in Human Motion via Mix-and-Match Perturbation.

Mohammad Sadegh Aliakbarian, Fatemeh Sadat Saleh, Mathieu Salzmann, Lars Petersson, Stephen Gould, AmirHossein Habibian

CoRR, 2019

2018

Incorporating Network Built-in Priors in Weakly-Supervised Semantic Segmentation.

Fatemehsadat Saleh, Mohammad Sadegh Ali Akbarian, Mathieu Salzmann, Lars Petersson, José M. Álvarez, Stephen Gould

IEEE Trans. Pattern Anal. Mach. Intell., 2018

VIENA2: A Driving Anticipation Dataset.

Mohammad Sadegh Aliakbarian, Fatemeh Sadat Saleh, Mathieu Salzmann, Basura Fernando, Lars Petersson, Lars Andersson

CoRR, 2018

Effective Use of Synthetic Data for Urban Scene Semantic Segmentation.

Fatemeh Sadat Saleh, Mohammad Sadegh Aliakbarian, Mathieu Salzmann, Lars Petersson, José M. Álvarez

Proceedings of the Computer Vision - ECCV 2018, 2018

VIENA ^2 : A Driving Anticipation Dataset.

Mohammad Sadegh Aliakbarian, Fatemeh Sadat Saleh, Mathieu Salzmann, Basura Fernando, Lars Petersson, Lars Andersson

Proceedings of the Computer Vision - ACCV 2018, 2018

2017

Incorporating Network Built-in Priors in Weakly-supervised Semantic Segmentation.

Fatemehsadat Saleh, Mohammad Sadegh Ali Akbarian, Mathieu Salzmann, Lars Petersson, Jose M. Alvarez, Stephen Gould

CoRR, 2017

Bringing Background into the Foreground: Making All Classes Equal in Weakly-Supervised Video Semantic Segmentation.

Fatemehsadat Saleh, Mohammad Sadegh Ali Akbarian, Mathieu Salzmann, Lars Petersson, Jose M. Alvarez

Proceedings of the IEEE International Conference on Computer Vision, 2017

Encouraging LSTMs to Anticipate Actions Very Early.

Mohammad Sadegh Ali Akbarian, Fatemehsadat Saleh, Mathieu Salzmann, Basura Fernando, Lars Petersson, Lars Andersson

Proceedings of the IEEE International Conference on Computer Vision, 2017

2016

Deep Action- and Context-Aware Sequence Learning for Activity Recognition and Anticipation.

Mohammad Sadegh Ali Akbarian, Fatemehsadat Saleh, Basura Fernando, Mathieu Salzmann, Lars Petersson, Lars Andersson

CoRR, 2016

Built-in Foreground/Background Prior for Weakly-Supervised Semantic Segmentation.

Fatemehsadat Saleh, Mohammad Sadegh Ali Akbarian, Mathieu Salzmann, Lars Petersson, Stephen Gould, Jose M. Alvarez

Proceedings of the Computer Vision - ECCV 2016, 2016