I'm presently working as Principal Researcher (AI) at KLASS, Singapore. Previously, I worked as Research Scientist in the Institute for Infocomm Research (I2R) division of A*STAR, Singapore.

I obtained my Ph.D. from the National Univeristy of Singapore under the joint supervision of Prof. Robby T. Tan and Prof. Loong-Fah Cheong. I've also worked in collaboration with Dr. Lionel Heng from DSO National Labortories, Singapore. My primary research interests include Computer Vision and Deep Learning.

Prior to Ph.D., I worked as Sr. Design Engineer at Freescale Semiconductors, India. I obtained my B.Eng. from Delhi College of Engineering, University of Delhi, India.

Research

My previous research works were dedicated to: (1) Handling low-level vision problems such as depth from stereo and optical flow estimation, and (2) Performing visibility enhancement, under degraded visibility conditions such as nighttime and daytime fog. Related publications are presented below.

	DC-ShadowNet: Single-Image Hard and Soft Shadow Removal Using Unsupervised Domain-Classifier Guided Network Yeying Jin, Aashish Sharma, Robby T. Tan International Conference on Computer Vision (ICCV), 2021, Montreal, Canada paper | bibtex | code
	Nighttime Visibility Enhancement by Increasing the Dynamic Range and Suppression of Light Effects Aashish Sharma, Robby T. Tan Computer Vision and Pattern Recognition (CVPR), 2021, Nashville, USA paper | bibtex | data
	Nighttime Stereo Depth Estimation using Joint Translation-Stereo Learning: Light Effects and Uninformative Regions [Oral] Aashish Sharma, Loong-Fah Cheong, Lionel Heng, Robby T. Tan International Conference on 3D Vision (3DV), 2020, Fukuoka, Japan paper | bibtex | arXiv'19 | code (arXiv'19)
	Single-Image Camera Response Function Using Prediction Consistency and Gradual Refinement Aashish Sharma, Robby T. Tan, Loong-Fah Cheong Asian Conference on Computer Vision (ACCV), 2020, Kyoto, Japan paper | bibtex | code
	Optical Flow in Dense Foggy Scenes using Semi-Supervised Learning Wending Yan*, Aashish Sharma*, Robby T. Tan (*equal contribution) Computer Vision and Pattern Recognition (CVPR), 2020, Seattle, USA paper | bibtex | code Optical flow estimation under dense fog conditions via domain adaptive semi-supervised learning using labelled synthetic and unlabelled real fog data.
	Into the Twilight Zone: Depth Estimation using Joint Structure-Stereo Optimization Aashish Sharma, Loong-Fah Cheong European Conference on Computer Vision (ECCV), 2018, Munich, Germany paper | poster | bibtex Depth estimation for weakly-lit nighttime images by optimizing a joint structure-structure model.

Academic Services

Reviewer: ECCV’22, CVPR’22, IJCV’22, 3DV’21, MVA’21, IJCV’20, PSIVT’19, CVPR-V4AS’19

Education

• Feb’2017-May’2021: Ph.D. (Computer Vision and Deep Learning), NUS, Singapore
• Aug’2008-Jun’2012: B.Eng.(Electronics and Communication), DCE, Delhi University, India

Work Experience

• Jan’2023- : Principal Researcher (AI) at KLASS, Singapore
• Jun’2021-Jan’2023: Research Scientist at I2R, A*STAR, Singapore
• Feb’2017-May’2021: Research Engineer at NUS, Singapore
• Jun’2012-May’2016: Sr. Design Engineer at Freescale Semiconductors, India