Krishna Kumar Singh

Senior Research Scientist and Manager
Adobe Research

Email: krishsin[at]adobe.com

I am a senior research scientist and manager at Adobe Research. My research focuses on developing generative model for image generation and editing. Recently, I have been focusing on generating and editing complex scenes and objects. I am also working on image editing models for inpainting and outpaitning tasks which is currently used as Generative Fill in Photoshop and Firefly.

I got Phd in Computer Science from University of California, Davis under guidance of Prof. Yong Jae Lee. Previously, I finished my Masters in Robotics at Carnegie Mellon University, advised by Prof. Alexei Efros and Prof. Kayvon Fatahalian. I did undergrad in Computer Science and Engineering at IIIT Hyderabad under supervision of Prof. P J Narayanan.

I was research intern at Intel Labs and was Carnegie Mellon’s Robotics Institute Summer Scholar (RISS) under Prof. Martial Hebert. I also interned at Allen Institute for Artificial Intelligence (AI2) with Dr. Santosh Divvala and Prof. Ali Farhadi. I was a research intern at Facebook AI this summer and worked with Dr. Deepti Ghadiyaram, Dr. Dhruv Mahajan , Dr. Matt Feiszli, and Prof. Kristen Grauman.

Resume/Linkedin/Google-Scholar

Internship: If you are interested in doing research project with me at Adobe, please send me an email with your resume.

Product / Industry

	Generative Fill and Expand in Photoshop and Firefly Core researcher for modeling of Generative Fill and Expand Awarded by TIME as one of best inventions of 2023
	Skin Smoothing Neural Filter in Photoshop
	Strike a Pose Adobe Max Sneaks, 2021

Papers

	P2D: Plug and Play Discriminator for accelerating GAN frameworks Min Jin Chong, Krishna Kumar Singh,Yijun Li, Jingwan Lu, David Forsyth Winter Conference on Applications of Computer Vision (WACV), 2024
	Discovering and Mitigating Biases in CLIP-based Image Editing Md Mehrab Tanjim, Krishna Kumar Singh, Kushal Kafle, Ritwik Sinha, Garrison W. Cottrell Winter Conference on Applications of Computer Vision (WACV), 2024
	Consistent Multimodal Generation via A Unified GAN Framework Zhen Zhu, Yijun Li, Weijie Lyu, Krishna Kumar Singh , Zhixin Shu, Sören Pirk, Derek Hoiem Winter Conference on Applications of Computer Vision (WACV), 2024
	Towards Enhanced Controllability of Diffusion Models Wonwoong Cho, Hareesh Ravi, Midhun Harikumar, Vinh Khuc, Krishna Kumar Singh, Jingwan Lu, David I Inouye, Ajinkya Kale Arxiv, 2023
	UMFuse: Unified Multi View Fusion for Human Editing applications Rishabh Jain, Mayur Hemani, Duygu Ceylan, Krishna Kumar Singh, Jingwan Lu, Mausoom Sarkar, Balaji Krishnamurthy Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2023
	Zero-shot Image-to-Image Translation Gaurav Parmar, Krishna Kumar Singh, Richard Zhang, Yijun Li, Jingwan Lu, Jun-Yan Zhu ACM Transactions on Graphics (SIGGRAPH), 2023
	Modulating Pretrained Diffusion Models for Multimodal Image Synthesis Cusuh Ham, James Hays, Jingwan Lu, Krishna Kumar Singh, Zhifei Zhang, Tobias Hinz ACM Transactions on Graphics (SIGGRAPH), 2023
	Putting People in Their Place: Affordance-Aware Human Insertion into Scenes Sumith Kulal, Tim Brooks, Alex Aiken, Jiajun Wu, Jimei Yang, Jingwan Lu, Alexei A Efros, Krishna Kumar Singh IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023
	VGFlow: Visibility guided Flow Network for Human Reposing Rishabh Jain, Krishna Kumar Singh, Mayur Hemani, Jingwan Lu, Mausoom Sarkar, Duygu Ceylan, Balaji Krishnamurthy IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023
	Complete 3D Human Reconstruction from a Single Incomplete Image Junying Wang, Jae Shin Yoon, Tuanfeng Y. Wang, Krishna Kumar Singh, and Ulrich Neumann IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023
	Debiasing Image-to-Image Translation Models Md Mehrab Tanjim, Krishna Kumar Singh, Kushal Kafle, Ritwik Sinha, Garrison W. Cottrell British Machine Vision Conference (BMVC), 2022
	Contrastive Learning for Diverse Disentangled Foreground Generation Yuheng Li, Yijun Li, Jingwan Lu, Eli Shechtman, Yong Jae Lee, Krishna Kumar Singh European Conference on Computer Vision (ECCV) , 2022
	Discovering and Mitigating Biases in CLIP-based Text-to-Image Generation Md Mehrab Tanjim, Krishna Kumar Singh, Kushal Kafle, Ritwik Sinha, Garrison W. Cottrell European Conference on Computer Vision (ECCV) Worshop, 2022
	Spatially-Adaptive Multilayer Selection for GAN Inversion and Editing Gaurav Parmar, Yijun Li, Jingwan Lu, Richard Zhang, Jun-Yan Zhu, Krishna Kumar Singh IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022
	GIRAFFE HD: A High-Resolution 3D-aware Generative Model Yang Xue, Yuheng Li, Krishna Kumar Singh , Yong Jae Lee IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022
	InsetGAN for Full-Body Image Generation Anna Frühstück, Krishna Kumar Singh, Eli Shechtman, Niloy J. Mitra, Peter Wonka, Jingwan Lu IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022
	Generating and Controlling Diversity in Image Search Md Mehrab Tanjim, Ritwik Sinha, Krishna Kumar Singh , Sridhar Mahadevan, David Arbour, Moumita Sinha, Garrison W. Cottrell Winter Conference on Applications of Computer Vision (WACV), 2022
	Dance In the Wild: Monocular Human Animation with Neural Dynamic Appearance Synthesis Tuanfeng Y. Wang, Duygu Ceylan, Krishna Kumar Singh, Niloy J. Mitra International Conference on 3D Vision (3DV), 2021 (oral presentation)
	PartGAN: Weakly-supervised Part Decomposition for Image Generation and Segmentation Yuheng Li, Krishna Kumar Singh , Yang Xue, Yong Jae Lee British Machine Vision Conference (BMVC), 2021
	Collaging Class-specific GANs for Semantic Image Synthesis Yuheng Li, Yijun Li, Jingwan Lu, Eli Shechtman, Yong Jae Lee, Krishna Kumar Singh Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2021
	Seeing the Unseen: Predicting the First-Person Camera Wearer's Location and Pose in Third-Person Scenes Yangming Wen, Krishna Kumar Singh, Markham Anderson, Wei-Pang Jan, Yong Jae Lee International Workshop on Egocentric Perception, Interaction and Computing (EPIC), ICCV 2021
	IMAGINE: Image Synthesis by Image-Guided Model Inversion Pei Wang, Yijun Li, Krishna Kumar Singh, Jingwan Lu, Nuno Vasconcelos IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021
	Generating Furry Cars: Disentangling Object Shape and Appearance across Multiple Domains Utkarsh Ojha, Krishna Kumar Singh, Yong Jae Lee International Conference on Learning Representations (ICLR), 2021
	Elastic-InfoGAN: Unsupervised Disentangled Representation Learning in Class-Imbalanced Data Utkarsh Ojha, Krishna Kumar Singh, Cho-Jui Hsieh, Yong Jae Lee Conference on Neural Information Processing Systems (NeurIPS), 2020
	Don’t Judge an Object by Its Context: Learning to Overcome Contextual Bias Krishna Kumar Singh, Dhruv Mahajan, Kristen Grauman, Yong Jae Lee, Matt Feiszli, Deepti Ghadiyaram IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020 Oral Presentation
	MixNMatch: Multifactor Disentanglement and Encoding for Conditional Image Generation Yuheng Li, Krishna Kumar Singh, Utkarsh Ojha, Yong Jae Lee IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020
	FineGAN: Unsupervised Hierarchical Disentanglement for Fine-Grained Object Generation and Discovery Krishna Kumar Singh, Utkarsh Ojha, Yong Jae Lee IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 * equal contribution Oral Presentation
	You reap what you sow: Using Videos to Generate High Precision Object Proposals for Weakly-supervised Object Detection Krishna Kumar Singh, Yong Jae Lee IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019
	DOCK: Detecting Objects by transferring Common-sense Knowledge Krishna Kumar Singh, Santosh Divvala, Ali Farhadi, Yong Jae Lee European Conference on Computer Vision (ECCV), 2018
	Who Will Share My Image? Predicting the Content Diffusion Path in Online Social Networks Wenjian Hu, Krishna Kumar Singh, Fanyi Xiao, Jinyoung Han, Chen-Nee Chuah, Yong Jae Lee ACM International Conference on Web Search and Data Mining (WSDM), 2018 * equal contribution
	Hide-and-Seek: Forcing a Network to be Meticulous for Weakly-supervised Object and Action Localization Krishna Kumar Singh, Yong Jae Lee International Conference on Computer Vision (ICCV), 2017 Hide-and-Seek: A Data Augmentation Technique for Weakly-Supervised Localization and Beyond Krishna Kumar Singh, Hao Yu, Aron Sarmasi, Gautam Pradeep, Yong Jae Lee Arxiv, 2018
	Identifying First-Person Camera Wearers in Third-Person Videos C. Fan, J. Lee, M. Xu, K. K. Singh , Y. J. Lee, D. J. Crandall, and M. S. Ryoo IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
	End-to-End Localization and Ranking for Relative Attributes Krishna Kumar Singh, Yong Jae Lee European Conference on Computer Vision (ECCV), 2016
	Track and Transfer: Watching Videos to Simulate Strong Human Supervision for Weakly-Supervised Object Detection Krishna Kumar Singh, Fanyi Xiao, Yong Jae Lee IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016
	KrishnaCam: Using a Longitudinal, Single-Person, Egocentric Dataset for Scene Understanding Tasks Krishna Kumar Singh, Kayvon Fatahalian, Alexei A. Efros Winter Conference on Applications of Computer Vision (WACV), 2016
	Storytelling Patches: Predicting Tourist Spots in a City Aayush Bansal, Krishna Kumar Singh ECCV Workshop on Storytelling with Images and Videos (VisStory), 2014
	Geometry Directed Browser for Personal Photographs Aditya Deshpande, Siddharth Choudhary, P J Narayanan, Krishna Kumar Singh, Kaustav Kundu, Aditya Singh, Apurva Kumar ACM Indian Conference On Vision, Graphics And Image Processing (ICVGIP), 2012 (oral presentation) [Video]
	Hybrid Multi-Core Algorithms for Regular Image Filtering Applications Shrenik Lad, Krishna Kumar Singh, Kishore Kothapalli, P J Narayanan IEEE International Conference on High Performance Computing (HiPC) Student Research Symposium, 2012 (NVIDIA Best GPU Poster Award) [Poster]

Present/Past Interns

Yuheng Li (UW–Madison)
Liming Jiang (NTU)
Zhipeng Bao (CMU)
Boxiao Pan (Stanford)
Yuming Jiang (NTU)
Nannan Li (Boston University)
Gaurav Parmar (CMU)
Sumith Kulal (Stanford)
Min Jin Chong (UIUC)
Zhen Zhu (UIUC)
Cusuh Ham (Georgia Tech)
Junying Wang (USC)
Wonwoong Cho (Purdue)
Mehrab Tanjim (UCSD)
Anna Frühstück (KAUST)
Bowen Li (Oxford)
Pei Wang (UCSD)

Work Experience

	Research Scientist and Manager at Adobe Research
	Research Intern at Facebook AI (Summer 2019) Worked on removing contextual bias in visual recognition.
	Research Intern at Allen Institute for Artificial Intelligence (Summer 2017) Worked on improving object detection by transferring common-sense knowledge.
	Computer Vision Intern at Intel Labs (Summer 2015) Worked on Video Summarization and Retrieval. Filed two patents.
	Carnegie Mellon’s Robotics Institute Summer Scholar (RISS) under Prof. Martial Hebert (Summer 2012) Worked on Object Recognition in Different Illumination Conditions. [Poster]