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2020 – today
- 2024
[c64]Peter Schaldenbrand, Gaurav Parmar, Jun-Yan Zhu, James McCann, Jean Oh:
CoFRIDA: Self-Supervised Fine-Tuning for Human-Robot Co-Painting. ICRA 2024: 2296-2302- [i72]Kangle Deng, Timothy Omernick, Alexander Weiss, Deva Ramanan, Jun-Yan Zhu, Tinghui Zhou, Maneesh Agrawala:
FlashTex: Fast Relightable Mesh Texturing with LightControlNet. CoRR abs/2402.13251 (2024) - [i71]Peter Schaldenbrand, Gaurav Parmar, Jun-Yan Zhu, James McCann, Jean Oh:
CoFRIDA: Self-Supervised Fine-Tuning for Human-Robot Co-Painting. CoRR abs/2402.13442 (2024) - [i70]Or Patashnik, Rinon Gal, Daniel Cohen-Or, Jun-Yan Zhu, Fernando De la Torre:
Consolidating Attention Features for Multi-view Image Editing. CoRR abs/2402.14792 (2024) - [i69]Gaurav Parmar, Taesung Park, Srinivasa Narasimhan, Jun-Yan Zhu:
One-Step Image Translation with Text-to-Image Models. CoRR abs/2403.12036 (2024) - [i68]Nupur Kumari, Grace Su, Richard Zhang, Taesung Park, Eli Shechtman, Jun-Yan Zhu:
Customizing Text-to-Image Diffusion with Camera Viewpoint Control. CoRR abs/2404.12333 (2024) - [i67]Songwei Ge, Aniruddha Mahapatra, Gaurav Parmar, Jun-Yan Zhu, Jia-Bin Huang:
On the Content Bias in Fr\'echet Video Distance. CoRR abs/2404.12391 (2024) - [i66]Maxwell Jones, Sheng-Yu Wang, Nupur Kumari, David Bau, Jun-Yan Zhu:
Customizing Text-to-Image Models with a Single Image Pair. CoRR abs/2405.01536 (2024) - [i65]Minguk Kang, Richard Zhang, Connelly Barnes, Sylvain Paris, Suha Kwak, Jaesik Park, Eli Shechtman, Jun-Yan Zhu, Taesung Park:
Distilling Diffusion Models into Conditional GANs. CoRR abs/2405.05967 (2024) - [i64]Sheng-Yu Wang, Aaron Hertzmann, Alexei A. Efros, Jun-Yan Zhu, Richard Zhang:
Data Attribution for Text-to-Image Models by Unlearning Synthesized Images. CoRR abs/2406.09408 (2024) - 2023
- [j17]Jun-Yan Zhu, Han-Lu He, Xiao-Chun Jiang, Hai-Wei Bao, Fen Chen:
Multimodal ultrasound features of breast cancers: correlation with molecular subtypes. BMC Medical Imaging 23(1): 57 (2023) - [j16]Muyang Li
, Ji Lin, Chenlin Meng, Stefano Ermon, Song Han, Jun-Yan Zhu:
Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models. IEEE Trans. Pattern Anal. Mach. Intell. 45(12): 14465-14480 (2023) - [j15]Aniruddha Mahapatra, Aliaksandr Siarohin, Hsin-Ying Lee, Sergey Tulyakov, Jun-Yan Zhu:
Text-Guided Synthesis of Eulerian Cinemagraphs. ACM Trans. Graph. 42(6): 259:1-259:13 (2023) - [c63]Nupur Kumari, Bingliang Zhang, Richard Zhang, Eli Shechtman, Jun-Yan Zhu:
Multi-Concept Customization of Text-to-Image Diffusion. CVPR 2023: 1931-1941 - [c62]George Cazenavette, Tongzhou Wang, Antonio Torralba, Alexei A. Efros, Jun-Yan Zhu:
Generalizing Dataset Distillation via Deep Generative Prior. CVPR 2023: 3739-3748 - [c61]Kangle Deng, Gengshan Yang, Deva Ramanan, Jun-Yan Zhu:
3D-aware Conditional Image Synthesis. CVPR 2023: 4434-4445 - [c60]Minguk Kang, Jun-Yan Zhu, Richard Zhang, Jaesik Park, Eli Shechtman, Sylvain Paris, Taesung Park:
Scaling up GANs for Text-to-Image Synthesis. CVPR 2023: 10124-10134 - [c59]Yotam Nitzan, Michaël Gharbi, Richard Zhang, Taesung Park, Jun-Yan Zhu, Daniel Cohen-Or, Eli Shechtman:
Domain Expansion of Image Generators. CVPR 2023: 15933-15942 - [c58]Ruihan Gao, Wenzhen Yuan, Jun-Yan Zhu:
Controllable Visual-Tactile Synthesis. ICCV 2023: 7017-7029 - [c57]Sheng-Yu Wang, Alexei A. Efros, Jun-Yan Zhu, Richard Zhang:
Evaluating Data Attribution for Text-to-Image Models. ICCV 2023: 7158-7169 - [c56]Songwei Ge, Taesung Park, Jun-Yan Zhu, Jia-Bin Huang:
Expressive Text-to-Image Generation with Rich Text. ICCV 2023: 7511-7522 - [c55]Yunji Kim, Jiyoung Lee, Jin-Hwa Kim, Jung-Woo Ha, Jun-Yan Zhu:
Dense Text-to-Image Generation with Attention Modulation. ICCV 2023: 7667-7677 - [c54]Chonghyuk Song, Gengshan Yang, Kangle Deng, Jun-Yan Zhu, Deva Ramanan:
Total-Recon: Deformable Scene Reconstruction for Embodied View Synthesis. ICCV 2023: 17625-17636 - [c53]Nupur Kumari, Bingliang Zhang, Sheng-Yu Wang, Eli Shechtman, Richard Zhang, Jun-Yan Zhu:
Ablating Concepts in Text-to-Image Diffusion Models. ICCV 2023: 22634-22645 - [c52]Hyunsu Kim, Gayoung Lee, Yunjey Choi, Jin-Hwa Kim, Jun-Yan Zhu:
3D-aware Blending with Generative NeRFs. ICCV 2023: 22849-22861 - [c51]Tony Lee, Michihiro Yasunaga, Chenlin Meng, Yifan Mai, Joon Sung Park, Agrim Gupta, Yunzhi Zhang, Deepak Narayanan, Hannah Teufel, Marco Bellagente, Minguk Kang, Taesung Park, Jure Leskovec, Jun-Yan Zhu, Fei-Fei Li, Jiajun Wu, Stefano Ermon, Percy Liang:
Holistic Evaluation of Text-to-Image Models. NeurIPS 2023 - [c50]Chenlin Meng, Jiaming Song, Shuang Li, Jun-Yan Zhu, Stefano Ermon, Tsung-Yi Lin, Chen-Hsuan Lin, Karsten Kreis:
SIGGRAPH 2023 Course on Diffusion Models. SIGGRAPH Courses 2023: 7:1-7:113 - [c49]Gaurav Parmar, Krishna Kumar Singh, Richard Zhang, Yijun Li, Jingwan Lu, Jun-Yan Zhu:
Zero-shot Image-to-Image Translation. SIGGRAPH (Conference Paper Track) 2023: 11:1-11:11 - [c48]Daohan Lu, Sheng-Yu Wang, Nupur Kumari, Rohan Agarwal, Mia Tang, David Bau, Jun-Yan Zhu:
Content-based Search for Deep Generative Models. SIGGRAPH Asia 2023: 71:1-71:12 - [i63]Yotam Nitzan, Michaël Gharbi, Richard Zhang, Taesung Park, Jun-Yan Zhu, Daniel Cohen-Or, Eli Shechtman:
Domain Expansion of Image Generators. CoRR abs/2301.05225 (2023) - [i62]Gaurav Parmar, Krishna Kumar Singh, Richard Zhang, Yijun Li, Jingwan Lu, Jun-Yan Zhu:
Zero-shot Image-to-Image Translation. CoRR abs/2302.03027 (2023) - [i61]Hyunsu Kim, Gayoung Lee, Yunjey Choi, Jin-Hwa Kim, Jun-Yan Zhu:
3D-aware Blending with Generative NeRFs. CoRR abs/2302.06608 (2023) - [i60]Kangle Deng, Gengshan Yang, Deva Ramanan, Jun-Yan Zhu:
3D-aware Conditional Image Synthesis. CoRR abs/2302.08509 (2023) - [i59]Minguk Kang, Jun-Yan Zhu, Richard Zhang, Jaesik Park, Eli Shechtman, Sylvain Paris, Taesung Park:
Scaling up GANs for Text-to-Image Synthesis. CoRR abs/2303.05511 (2023) - [i58]Nupur Kumari, Bingliang Zhang, Sheng-Yu Wang, Eli Shechtman, Richard Zhang, Jun-Yan Zhu:
Ablating Concepts in Text-to-Image Diffusion Models. CoRR abs/2303.13516 (2023) - [i57]Songwei Ge, Taesung Park, Jun-Yan Zhu, Jia-Bin Huang:
Expressive Text-to-Image Generation with Rich Text. CoRR abs/2304.06720 (2023) - [i56]Chonghyuk Song, Gengshan Yang, Kangle Deng, Jun-Yan Zhu, Deva Ramanan:
Total-Recon: Deformable Scene Reconstruction for Embodied View Synthesis. CoRR abs/2304.12317 (2023) - [i55]George Cazenavette, Tongzhou Wang, Antonio Torralba, Alexei A. Efros, Jun-Yan Zhu:
Generalizing Dataset Distillation via Deep Generative Prior. CoRR abs/2305.01649 (2023) - [i54]Ruihan Gao, Wenzhen Yuan, Jun-Yan Zhu:
Controllable Visual-Tactile Synthesis. CoRR abs/2305.03051 (2023) - [i53]Sheng-Yu Wang, Alexei A. Efros, Jun-Yan Zhu, Richard Zhang:
Evaluating Data Attribution for Text-to-Image Models. CoRR abs/2306.09345 (2023) - [i52]Aniruddha Mahapatra, Aliaksandr Siarohin, Hsin-Ying Lee, Sergey Tulyakov, Jun-Yan Zhu:
Synthesizing Artistic Cinemagraphs from Text. CoRR abs/2307.03190 (2023) - [i51]Yunji Kim, Jiyoung Lee, Jin-Hwa Kim, Jung-Woo Ha, Jun-Yan Zhu:
Dense Text-to-Image Generation with Attention Modulation. CoRR abs/2308.12964 (2023) - [i50]Tony Lee, Michihiro Yasunaga, Chenlin Meng, Yifan Mai, Joon Sung Park, Agrim Gupta, Yunzhi Zhang, Deepak Narayanan, Hannah Benita Teufel, Marco Bellagente, Minguk Kang, Taesung Park, Jure Leskovec, Jun-Yan Zhu, Li Fei-Fei, Jiajun Wu, Stefano Ermon, Percy Liang:
Holistic Evaluation of Text-To-Image Models. CoRR abs/2311.04287 (2023) - 2022
- [j14]Muyang Li, Ji Lin, Yaoyao Ding, Zhijian Liu, Jun-Yan Zhu, Song Han:
GAN Compression: Efficient Architectures for Interactive Conditional GANs. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 9331-9346 (2022) - [j13]Sheng-Yu Wang, David Bau, Jun-Yan Zhu:
Rewriting geometric rules of a GAN. ACM Trans. Graph. 41(4): 73:1-73:16 (2022) - [c47]George Cazenavette, Tongzhou Wang, Antonio Torralba, Alexei A. Efros, Jun-Yan Zhu:
Wearable ImageNet: Synthesizing Tileable Textures via Dataset Distillation. CVPR Workshops 2022: 2277-2281 - [c46]George Cazenavette, Tongzhou Wang, Antonio Torralba, Alexei A. Efros, Jun-Yan Zhu:
Dataset Distillation by Matching Training Trajectories. CVPR Workshops 2022: 4749-4758 - [c45]Nupur Kumari, Richard Zhang, Eli Shechtman, Jun-Yan Zhu:
Ensembling Off-the-shelf Models for GAN Training. CVPR 2022: 10641-10652 - [c44]George Cazenavette, Tongzhou Wang, Antonio Torralba, Alexei A. Efros, Jun-Yan Zhu:
Dataset Distillation by Matching Training Trajectories. CVPR 2022: 10708-10717 - [c43]Gaurav Parmar, Yijun Li, Jingwan Lu, Richard Zhang, Jun-Yan Zhu, Krishna Kumar Singh:
Spatially-Adaptive Multilayer Selection for GAN Inversion and Editing. CVPR 2022: 11389-11399 - [c42]Gaurav Parmar, Richard Zhang, Jun-Yan Zhu:
On Aliased Resizing and Surprising Subtleties in GAN Evaluation. CVPR 2022: 11400-11410 - [c41]Kangle Deng, Andrew Liu, Jun-Yan Zhu, Deva Ramanan:
Depth-supervised NeRF: Fewer Views and Faster Training for Free. CVPR 2022: 12872-12881 - [c40]William S. Peebles, Jun-Yan Zhu, Richard Zhang, Antonio Torralba, Alexei A. Efros, Eli Shechtman:
GAN-Supervised Dense Visual Alignment. CVPR 2022: 13460-13471 - [c39]Chenlin Meng, Yutong He, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, Stefano Ermon:
SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations. ICLR 2022 - [c38]Muyang Li, Ji Lin, Chenlin Meng, Stefano Ermon, Song Han, Jun-Yan Zhu:
Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models. NeurIPS 2022 - [i49]George Cazenavette, Tongzhou Wang, Antonio Torralba, Alexei A. Efros, Jun-Yan Zhu:
Dataset Distillation by Matching Training Trajectories. CoRR abs/2203.11932 (2022) - [i48]Gaurav Parmar, Yijun Li, Jingwan Lu, Richard Zhang, Jun-Yan Zhu, Krishna Kumar Singh:
Spatially-Adaptive Multilayer Selection for GAN Inversion and Editing. CoRR abs/2206.08357 (2022) - [i47]Sheng-Yu Wang, David Bau, Jun-Yan Zhu:
Rewriting Geometric Rules of a GAN. CoRR abs/2207.14288 (2022) - [i46]Daohan Lu, Sheng-Yu Wang, Nupur Kumari, Rohan Agarwal, David Bau, Jun-Yan Zhu:
Content-Based Search for Deep Generative Models. CoRR abs/2210.03116 (2022) - [i45]Muyang Li, Ji Lin, Chenlin Meng, Stefano Ermon, Song Han, Jun-Yan Zhu:
Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models. CoRR abs/2211.02048 (2022) - [i44]Nupur Kumari, Bingliang Zhang, Richard Zhang, Eli Shechtman, Jun-Yan Zhu:
Multi-Concept Customization of Text-to-Image Diffusion. CoRR abs/2212.04488 (2022) - 2021
- [c37]Ji Lin, Richard Zhang, Frieder Ganz, Song Han, Jun-Yan Zhu:
Anycost GANs for Interactive Image Synthesis and Editing. CVPR 2021: 14986-14996 - [c36]Lucy Chai, Jun-Yan Zhu, Eli Shechtman, Phillip Isola, Richard Zhang:
Ensembling With Deep Generative Views. CVPR 2021: 14997-15007 - [c35]Steven Liu, Xiuming Zhang, Zhoutong Zhang, Richard Zhang, Jun-Yan Zhu, Bryan Russell:
Editing Conditional Radiance Fields. ICCV 2021: 5753-5763 - [c34]Sheng-Yu Wang, David Bau, Jun-Yan Zhu:
Sketch Your Own GAN. ICCV 2021: 14030-14040 - [c33]Alex Andonian, Taesung Park, Bryan Russell, Phillip Isola, Jun-Yan Zhu, Richard Zhang:
Contrastive Feature Loss for Image Prediction. ICCVW 2021: 1934-1943 - [c32]Ayush Tewari, Ohad Fried, Justus Thies, Vincent Sitzmann, Stephen Lombardi, Zexiang Xu, Tomas Simon, Matthias Nießner, Edgar Tretschk, Lingjie Liu, Ben Mildenhall, Pratul P. Srinivasan, Rohit Pandey, Sergio Orts-Escolano, Sean Ryan Fanello, Michelle Guo, Gordon Wetzstein, Jun-Yan Zhu, Christian Theobalt, Maneesh Agrawala, Daniel B. Goldman, Michael Zollhöfer:
Advances in neural rendering. SIGGRAPH Courses 2021: 1:1-1:320 - [i43]Ji Lin, Richard Zhang, Frieder Ganz, Song Han, Jun-Yan Zhu:
Anycost GANs for Interactive Image Synthesis and Editing. CoRR abs/2103.03243 (2021) - [i42]Gaurav Parmar, Richard Zhang, Jun-Yan Zhu:
On Buggy Resizing Libraries and Surprising Subtleties in FID Calculation. CoRR abs/2104.11222 (2021) - [i41]Lucy Chai, Jun-Yan Zhu, Eli Shechtman, Phillip Isola, Richard Zhang:
Ensembling with Deep Generative Views. CoRR abs/2104.14551 (2021) - [i40]Steven Liu, Xiuming Zhang, Zhoutong Zhang, Richard Zhang, Jun-Yan Zhu, Bryan Russell:
Editing Conditional Radiance Fields. CoRR abs/2105.06466 (2021) - [i39]Kangle Deng, Andrew Liu, Jun-Yan Zhu, Deva Ramanan:
Depth-supervised NeRF: Fewer Views and Faster Training for Free. CoRR abs/2107.02791 (2021) - [i38]Chenlin Meng, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, Stefano Ermon:
SDEdit: Image Synthesis and Editing with Stochastic Differential Equations. CoRR abs/2108.01073 (2021) - [i37]Sheng-Yu Wang, David Bau, Jun-Yan Zhu:
Sketch Your Own GAN. CoRR abs/2108.02774 (2021) - [i36]Alex Andonian, Taesung Park, Bryan Russell, Phillip Isola, Jun-Yan Zhu, Richard Zhang:
Contrastive Feature Loss for Image Prediction. CoRR abs/2111.06934 (2021) - [i35]William S. Peebles, Jun-Yan Zhu, Richard Zhang, Antonio Torralba, Alexei A. Efros, Eli Shechtman:
GAN-Supervised Dense Visual Alignment. CoRR abs/2112.05143 (2021) - [i34]Nupur Kumari, Richard Zhang, Eli Shechtman, Jun-Yan Zhu:
Ensembling Off-the-shelf Models for GAN Training. CoRR abs/2112.09130 (2021) - 2020
- [j12]Ayush Tewari, Ohad Fried, Justus Thies, Vincent Sitzmann, Stephen Lombardi, Kalyan Sunkavalli, Ricardo Martin-Brualla, Tomas Simon, Jason M. Saragih, Matthias Nießner, Rohit Pandey, Sean Ryan Fanello, Gordon Wetzstein, Jun-Yan Zhu, Christian Theobalt, Maneesh Agrawala, Eli Shechtman, Dan B. Goldman, Michael Zollhöfer:
State of the Art on Neural Rendering. Comput. Graph. Forum 39(2): 701-727 (2020) - [j11]Jun-Yan Zhu, Hongsheng Li, Eli Shechtman, Ming-Yu Liu, Jan Kautz, Antonio Torralba:
Guest Editorial: Generative Adversarial Networks for Computer Vision. Int. J. Comput. Vis. 128(10): 2363-2365 (2020) - [j10]David Bau, Jun-Yan Zhu, Hendrik Strobelt, Àgata Lapedriza, Bolei Zhou, Antonio Torralba:
Understanding the role of individual units in a deep neural network. Proc. Natl. Acad. Sci. USA 117(48): 30071-30078 (2020) - [c31]Muyang Li, Ji Lin, Yaoyao Ding, Zhijian Liu, Jun-Yan Zhu, Song Han:
GAN Compression: Efficient Architectures for Interactive Conditional GANs. CVPR 2020: 5283-5293 - [c30]Steven Liu, Tongzhou Wang, David Bau, Jun-Yan Zhu, Antonio Torralba:
Diverse Image Generation via Self-Conditioned GANs. CVPR 2020: 14274-14283 - [c29]Minyoung Huh, Richard Zhang, Jun-Yan Zhu, Sylvain Paris, Aaron Hertzmann:
Transforming and Projecting Images into Class-Conditional Generative Networks. ECCV (2) 2020: 17-34 - [c28]Taesung Park, Alexei A. Efros, Richard Zhang, Jun-Yan Zhu:
Contrastive Learning for Unpaired Image-to-Image Translation. ECCV (9) 2020: 319-345 - [c27]David Bau, Steven Liu, Tongzhou Wang, Jun-Yan Zhu, Antonio Torralba:
Rewriting a Deep Generative Model. ECCV (1) 2020: 351-369 - [c26]William S. Peebles, John Peebles, Jun-Yan Zhu, Alexei A. Efros, Antonio Torralba:
The Hessian Penalty: A Weak Prior for Unsupervised Disentanglement. ECCV (6) 2020: 581-597 - [c25]Taesung Park, Jun-Yan Zhu, Oliver Wang, Jingwan Lu, Eli Shechtman, Alexei A. Efros, Richard Zhang:
Swapping Autoencoder for Deep Image Manipulation. NeurIPS 2020 - [c24]Shengyu Zhao, Zhijian Liu, Ji Lin, Jun-Yan Zhu, Song Han:
Differentiable Augmentation for Data-Efficient GAN Training. NeurIPS 2020 - [i33]Muyang Li, Ji Lin, Yaoyao Ding, Zhijian Liu, Jun-Yan Zhu, Song Han:
GAN Compression: Efficient Architectures for Interactive Conditional GANs. CoRR abs/2003.08936 (2020) - [i32]Ayush Tewari, Ohad Fried, Justus Thies, Vincent Sitzmann, Stephen Lombardi, Kalyan Sunkavalli, Ricardo Martin-Brualla, Tomas Simon, Jason M. Saragih, Matthias Nießner, Rohit Pandey, Sean Ryan Fanello, Gordon Wetzstein, Jun-Yan Zhu, Christian Theobalt, Maneesh Agrawala, Eli Shechtman, Dan B. Goldman, Michael Zollhöfer:
State of the Art on Neural Rendering. CoRR abs/2004.03805 (2020) - [i31]Minyoung Huh, Richard Zhang, Jun-Yan Zhu, Sylvain Paris, Aaron Hertzmann:
Transforming and Projecting Images into Class-conditional Generative Networks. CoRR abs/2005.01703 (2020) - [i30]David Bau, Hendrik Strobelt, William S. Peebles, Jonas Wulff, Bolei Zhou, Jun-Yan Zhu, Antonio Torralba:
Semantic Photo Manipulation with a Generative Image Prior. CoRR abs/2005.07727 (2020) - [i29]Steven Liu, Tongzhou Wang, David Bau, Jun-Yan Zhu, Antonio Torralba:
Diverse Image Generation via Self-Conditioned GANs. CoRR abs/2006.10728 (2020) - [i28]Shengyu Zhao, Zhijian Liu, Ji Lin, Jun-Yan Zhu, Song Han:
Differentiable Augmentation for Data-Efficient GAN Training. CoRR abs/2006.10738 (2020) - [i27]Taesung Park, Jun-Yan Zhu, Oliver Wang, Jingwan Lu, Eli Shechtman, Alexei A. Efros, Richard Zhang:
Swapping Autoencoder for Deep Image Manipulation. CoRR abs/2007.00653 (2020) - [i26]David Bau, Steven Liu, Tongzhou Wang, Jun-Yan Zhu, Antonio Torralba:
Rewriting a Deep Generative Model. CoRR abs/2007.15646 (2020) - [i25]Taesung Park, Alexei A. Efros, Richard Zhang, Jun-Yan Zhu:
Contrastive Learning for Unpaired Image-to-Image Translation. CoRR abs/2007.15651 (2020) - [i24]William S. Peebles, John Peebles, Jun-Yan Zhu, Alexei A. Efros, Antonio Torralba:
The Hessian Penalty: A Weak Prior for Unsupervised Disentanglement. CoRR abs/2008.10599 (2020) - [i23]David Bau, Jun-Yan Zhu, Hendrik Strobelt, Àgata Lapedriza, Bolei Zhou, Antonio Torralba:
Understanding the Role of Individual Units in a Deep Neural Network. CoRR abs/2009.05041 (2020)
2010 – 2019
- 2019
- [j9]Jun-Yan Zhu:
Learning to Synthesize and Manipulate Natural Images. IEEE Computer Graphics and Applications 39(2): 14-23 (2019) - [j8]Subramanian Sundaram, Petr Kellnhofer, Yunzhu Li, Jun-Yan Zhu, Antonio Torralba, Wojciech Matusik:
Learning the signatures of the human grasp using a scalable tactile glove. Nat. 569(7758): 698-702 (2019) - [j7]David Bau, Hendrik Strobelt, William S. Peebles, Jonas Wulff, Bolei Zhou, Jun-Yan Zhu, Antonio Torralba:
Semantic photo manipulation with a generative image prior. ACM Trans. Graph. 38(4): 59:1-59:11 (2019) - [c23]Taesung Park, Ming-Yu Liu, Ting-Chun Wang, Jun-Yan Zhu:
Semantic Image Synthesis With Spatially-Adaptive Normalization. CVPR 2019: 2337-2346 - [c22]Yunzhu Li, Jun-Yan Zhu, Russ Tedrake, Antonio Torralba:
Connecting Touch and Vision via Cross-Modal Prediction. CVPR 2019: 10609-10618 - [c21]David Bau, Jun-Yan Zhu, Jonas Wulff, William S. Peebles, Bolei Zhou, Hendrik Strobelt, Antonio Torralba:
Seeing What a GAN Cannot Generate. ICCV 2019: 4501-4510 - [c20]David Bau, Jun-Yan Zhu, Hendrik Strobelt, Bolei Zhou, Joshua B. Tenenbaum, William T. Freeman, Antonio Torralba:
GAN Dissection: Visualizing and Understanding Generative Adversarial Networks. ICLR (Poster) 2019 - [c19]David Bau, Jun-Yan Zhu, Hendrik Strobelt, Bolei Zhou, Joshua B. Tenenbaum, William T. Freeman, Antonio Torralba:
Visualizing and Understanding GANs. DGS@ICLR 2019 - [c18]Yunzhu Li, Jiajun Wu, Jun-Yan Zhu, Joshua B. Tenenbaum, Antonio Torralba, Russ Tedrake:
Propagation Networks for Model-Based Control Under Partial Observation. ICRA 2019: 1205-1211 - [i22]David Bau, Jun-Yan Zhu, Hendrik Strobelt, Bolei Zhou, Joshua B. Tenenbaum, William T. Freeman, Antonio Torralba:
Visualizing and Understanding Generative Adversarial Networks (Extended Abstract). CoRR abs/1901.09887 (2019) - [i21]Taesung Park, Ming-Yu Liu, Ting-Chun Wang, Jun-Yan Zhu:
Semantic Image Synthesis with Spatially-Adaptive Normalization. CoRR abs/1903.07291 (2019) - [i20]Yunzhu Li, Jun-Yan Zhu, Russ Tedrake, Antonio Torralba:
Connecting Touch and Vision via Cross-Modal Prediction. CoRR abs/1906.06322 (2019) - [i19]David Bau, Jun-Yan Zhu, Jonas Wulff, William S. Peebles, Hendrik Strobelt, Bolei Zhou, Antonio Torralba:
Seeing What a GAN Cannot Generate. CoRR abs/1910.11626 (2019) - 2018
- [c17]Ting-Chun Wang, Ming-Yu Liu, Jun-Yan Zhu, Andrew Tao, Jan Kautz, Bryan Catanzaro:
High-Resolution Image Synthesis and Semantic Manipulation With Conditional GANs. CVPR 2018: 8798-8807 - [c16]