Krishna Kumar Singh

Research Scientist

San Jose

Krishna joined Adobe Research in July 2020, working in the area of computer vision and deep learning.

He did his Ph.D. in Computer Science at the University of California, Davis under the supervision of Prof. Yong Jae Lee. Previously, he finished his Masters in Robotics at Carnegie Mellon University, advised by Prof. Alexei Efros and Prof. Kayvon Fatahalian. He did his undergrad in Computer Science and Engineering at IIIT Hyderabad.

His research focuses on developing visual recognition and image generation models with minimal human supervision. Recently, he has been working on unsupervised image generation and disentanglement by providing explicit control over the different fine-grained properties of an image. He is in general interested in generating and disentangling visual data but he is also passionate about other interesting visual recognition problems.

For more information about him, please visit his personal website.

Publications

Contrastive Learning for Diverse Disentangled Foreground Generation

Li, Y., Li, Y., Lu, J., Shechtman, E., Lee, Y., Singh, K. (Oct. 23, 2022)

European Conference on Computer Vision (ECCV'22)

InsetGAN for Full-Body Image Generation

Frühstück, A., Singh, K., Shechtman, E., Mitra, N., Wonka, P., Lu, J. (Jun. 19, 2022)

CVPR2022

Inverting and Editing Real Images with Spatially Varying and Automatic Latent Selection

Parmar, G., Li, Y., Lu, J., Zhang, R., Zhu, J., Singh, K. (Jun. 19, 2022)

CVPR2022

Generating and Controlling Diversity in Image Search

Tanjim, M., Sinha, R., Singh, K., Mahadevan, S., Arbour, D., Sinha, M., Cottrell, G. (Jan. 10, 2022)

WACV

Dance In the Wild: Monocular Human Animation with Neural Dynamic Appearance Synthesis

Wang, T., Ceylan, D., Singh, K., Mitra, N. (Dec. 3, 2021)

International Conference on 3D Vision 2021

Collaging Class-specific GANs for Semantic Image Synthesis

Li, Y., Li, Y., Lu, J., Shechtman, E., Lee, Y., Singh, K., Lu, J. (Oct. 13, 2021)

International Conference on Computer Vision (ICCV'21)

IMAGINE: Image Synthesis by Image-Guided Model Inversion

Wang, P., Li, Y., Singh, K., Lu, J., Vasconcelos, N. (Jun. 19, 2021)

CVPR2021

Elastic-InfoGAN: Unsupervised Disentangled Representation Learning in Class-Imbalanced Data

Ojha, U., Singh, K., Hsieh, C., Lee, Y. (Dec. 6, 2020)

Conference on Neural Information Processing Systems (NeurIPS)