Richard Zhang

Research Scientist

San Francisco

I am a Research Scientist at Adobe Research. My research interests are in computer vision, machine learning, deep learning, and sensor fusion. I was previously a PhD student at UC Berkeley, advised by Professor Alexei (Alyosha) Efros. I obtained my BS and MEng degrees from Cornell University in ECE. I also received the Adobe Fellowship Award in 2017.

My personal website is here.

Publications

GAN-Supervised Dense Visual Alignment (GANgealing)

Peebles, W., Zhu, J., Zhang, R., Torralba, A., Efros, A., Shechtman, E. (Jun. 24, 2022)

Computer Vision and Pattern Recognition (CVPR'22)

Ensembling Off-the-shelf Models for GAN Training

Kumari, N., Zhang, R., Shechtman, E., Zhu, J. (Jun. 23, 2022)

Computer Vision and Pattern Recognition (CVPR'22)

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

Spatially-Adaptive Pixelwise Networks for Fast Image Translation

Shaham, T., Gharbi, M., Zhang, R., Shechtman, E., Michaeli, T. (Jun. 23, 2021)

Computer Vision and Pattern Recognition (CVPR'21)

Few-shot Image Generation via Cross-domain Correspondence

Ojha, U., Li, Y., Lu, J., Efros, A., Lee, Y., Shechtman, E., Zhang, R. (Jun. 23, 2021)

Computer Vision and Pattern Recognition (CVPR'21)

Ensembling with Deep Generative Views

Chai, L., Zhu, J., Shechtman, E., Isola, P., Zhang, R. (Jun. 22, 2021)

Computer Vision and Pattern Recognition (CVPR'21)

CDPAM: Contrastive learning for perceptual audio similarity

Manocha, P., Jin, Z., Zhang, R., Finkelstein, A. (Jun. 9, 2021)

IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

Swapping Autoencoder for Deep Image Manipulation

Park, T., Zhu, J., Wang, O., Lu, J., Shechtman, E., Efros, A., Zhang, R. (Dec. 6, 2020)

Neurips 2020

Few-shot Image Generation via Self-adaptation

Li, Y., Zhang, R., Lu, J., Shechtman, E. (Dec. 6, 2020)

Neurips 2020

A Differentiable Perceptual Audio Metric Learned from Just Noticeable Differences

Manocha, P., Finkelstein, A., Zhang, R., Bryan, N., Mysore, G., Jin, Z. (Oct. 26, 2020)

Interspeech 2020

Transforming and Projecting Images into Class-conditional Generative Networks

Huh, M., Zhang, R., Zhu, J., Paris, S., Hertzmann, A. (Aug. 23, 2020)

Oral

European Conference on Computer Vision (ECCV)

Deep Parametric Shape Predictions using Distance Fields

Smirnov, D., Fisher, M., Kim, V., Zhang, R., Solomon, J. (Jun. 1, 2020)

IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

CNN-generated images are surprisingly easy to spot… for now

Wang, S., Wang, O., Zhang, R., Owens, A., Efros, A. (Jun. 1, 2020)

Oral

IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Image Morphing with Perceptual Constraints and STN Alignment

Fish, N., Zhang, R., Perry, L., Cohen-Or, D., Shechtman, E., Barnes, C. (May. 1, 2020)

Computer Graphics Forum (CGF)

Detecting Photoshopped Images by Scripting Photoshop

Wang, S., Wang, O., Owens, A., Zhang, R., Efros, A. (Oct. 31, 2019)

International Conference on Computer Vision (ICCV'19)

Interactive Sketch & Fill: Multiclass Sketch-to-Image Translation

Ghosh, A., Zhang, R., Dokania, P., Efros, A., Torr, P., Wang, O., Shechtman, E. (Oct. 29, 2019)

International Conference on Computer Vision (ICCV'19)

Making Convolutional Networks Shift-Invariant Again

Zhang, R. (Jun. 12, 2019)

International Conference on Machine Learning (ICML'19)

The Unreasonable Effectiveness of Deep Features as a Perceptual Metric

Zhang, R., Isola, P., Efros, A., Shechtman, E., Wang, O. (Jun. 19, 2018)

IEEE Conference on Computer Vision and Pattern Recognition (CVPR'18)

Toward Multimodal Image-to-Image Translation

Zhu, J., Zhang, R., Pathak, D., Darrell, T., Efros, A., Wang, O., Shechtman, E. (Dec. 4, 2017)

Neural Information Processing Systems (NIPS'17)

News