Kuldeep Kulkarni

I am a research scientist in Adobe Research, Bengaluru, India. Before that I did a post-doc stint at Carnegie Mellon University where I worked with Aswin Sankaranarayanan. I received my PhD in Electrical Engineering from Arizona State University under the supervision of Pavan Turaga. Prior to that, I received my undergraduate degree in Electrical Engineering from the National Institute of Technology Karnataka, Surathkal, India in 2009. I hail from Ilkal, a tiny little town in India, where I spent 18 wonderful years.

Product Impact: Our image animation technology, "Moving Elements", that is inspired by our CVPR 2022 paper is shipped to and is available in Adobe Photoshop Elements 2023.

Openings: I am always looking for grad student interns who are passionate about becoming friends with pixels. Interested candidates may email me their resumes.

Email / Google Scholar / Resume (not updated) / LinkedIn / Twitter /

Research

My current research interests are in the areas of computer vision, specifically image and video synthesis and editing. Below are some of the projects I have worked on.

	Composing Parts for Expressive Object Generation Harsh Rangwani, Aishwarya Agarwal, Kuldeep Kulkarni, R Venkatesh Babu, Srikrishna Karanam Computer Vision and Pattern Recognition (CVPR) 2025 Paper
	ImPoster: Text and Frequency Guidance for Subject Driven Action Personalization using Diffusion Models Divya Kothandaraman, Kuldeep Kulkarni, Sumit Shekhar, Balaji Vasan Srinivasan, Dinesh Manocha International Conference on Computational Linguistics (COLING) 2025 Paper
	Polynomial Implicit Neural Framework for Promoting Shape Awareness in Generative Models Utkarsh Nath, Rajhans Singh, Ankita Shukla, Kuldeep Kulkarni, Pavan Turaga International Journal of Computer Vision (IJCV) 2024 Paper
	Blowing in the Wind: CycleNet for Human Cinemagraphs from Still Images Hugo Bertiche, Niloy J. Mitra, Kuldeep Kulkarni, Chun-Hao Paul Huang, Tuanfeng Y. Wang, Meysam Madadi, Sergio Escalera, Duygu Ceylan Computer Vision and Pattern Recognition (CVPR) 2023 Project Page
	Self-supervised Multi-view Disentanglement for Expansion of Visual Collections Praneetha Vaddamanu, Nihal Jain, Paridhi Maheshwari, Vishwa Vinay, Kuldeep Kulkarni Web Search and Data Mining (WSDM) 2023 Paper
	GEMS: Scene Expansion using Generative Models of Graphs Rishi Agarwal^, Tirupathi Saketh Chandra^, Vaidehi Patil^, Aniruddha Mahapatra^, Kuldeep Kulkarni, Vishwa Vinay Winter Conference on Applications of Computer Vision (WACV) 2023 Paper/Poster
	Controllable Animation of Fluid Elements in Still Images Aniruddha Mahapatra, Kuldeep Kulkarni Computer Vision and Pattern Recognition (CVPR) 2022 Project Page
	SemIE: Semantically-aware Image Extrapolation Bholeshwar Khurana, Soumya Ranjan Dash, Abhishek Bhatia, Aniruddha Mahapatra, Hrituraj Singh, Kuldeep Kulkarni International Conference on Computer Vision (ICCV) 2021 Project Page
	Halluci-Net: Scene Completion by Exploiting Object Co-occurrence Relationships Kuldeep Kulkarni, Tejas Gokhale, Rajhans Singh, Pavan Turaga, Aswin Sankaranarayanan AICC CVPR workshop 2021
	Convolutional Neural Networks for Noniterative Reconstruction of Compressively Sensed Images Suhas Lohit, Kuldeep Kulkarni, Ronan Kerviche, Pavan Turaga, Amit Ashok IEEE Transactions on Computational Imaging 2018 Code
	Weakly Supervised Learning of Heterogeneous Concepts in Videos Sohil Shah, Kuldeep Kulkarni, Arijit Biswas, Ankit Gandhi, Om Deshmukh, Larry Davis European Conference on Computer Vision (ECCV) 2016 Code/Poster
	ReconNet: Non-Iterative Reconstruction of Images from Compressively Sensed Measurements Kuldeep Kulkarni, Suhas Lohit, Pavan Turaga, Ronan Kerviche, Amit Ashok The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016 Project Page (Code available now). This work was covered by 'Nuit Blanche'
	Fast Integral Image Estimation at 1% measurement rate Kuldeep Kulkarni, Pavan Turaga under revisions at IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) , 2016 arXiv:1601.07258 [cs.CV]
	Direct Inference on Compressive Measurements using Convolutional Neural Networks Suhas Lohit, Kuldeep Kulkarni, Pavan Turaga International Conference on Image Processing, 2016
	Reconstruction-free action inference from compressive imagers Kuldeep Kulkarni, Pavan Turaga IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)(Impact factor: 5.781, Accepted on July 31, 2015) supplement
	Reconstruction-free Inference on Compressive Measurements Suhas Lohit, Kuldeep Kulkarni, Pavan Turaga, Jian Wang , Aswin Sankaranarayanan 4th IEEE Workshop on Computational Cameras and Displays (CCD), held in conjunction with IEEE CVPR, June 2015 (Best Paper Award) Presentation
	Recurrence Textures for Activity Recognition from compressive cameras Kuldeep Kulkarni, Pavan Turaga IEEE International Conference on Image Processing, 2012