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2020 – today
- 2023
[i54]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)- [i53]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) - [i52]Hyunsu Kim, Gayoung Lee, Yunjey Choi, Jin-Hwa Kim, Jun-Yan Zhu:
3D-aware Blending with Generative NeRFs. CoRR abs/2302.06608 (2023) - [i51]Kangle Deng, Gengshan Yang, Deva Ramanan, Jun-Yan Zhu:
3D-aware Conditional Image Synthesis. CoRR abs/2302.08509 (2023) - [i50]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) - 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) - [c46]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 - [c45]George Cazenavette, Tongzhou Wang, Antonio Torralba, Alexei A. Efros, Jun-Yan Zhu:
Dataset Distillation by Matching Training Trajectories. CVPR Workshops 2022: 4749-4758 - [c44]Nupur Kumari, Richard Zhang, Eli Shechtman, Jun-Yan Zhu:
Ensembling Off-the-shelf Models for GAN Training. CVPR 2022: 10641-10652 - [c43]George Cazenavette, Tongzhou Wang, Antonio Torralba, Alexei A. Efros, Jun-Yan Zhu:
Dataset Distillation by Matching Training Trajectories. CVPR 2022: 10708-10717 - [c42]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 - [c41]Gaurav Parmar, Richard Zhang, Jun-Yan Zhu:
On Aliased Resizing and Surprising Subtleties in GAN Evaluation. CVPR 2022: 11400-11410 - [c40]Kangle Deng, Andrew Liu, Jun-Yan Zhu, Deva Ramanan:
Depth-supervised NeRF: Fewer Views and Faster Training for Free. CVPR 2022: 12872-12881 - [c39]William S. Peebles, Jun-Yan Zhu, Richard Zhang, Antonio Torralba, Alexei A. Efros, Eli Shechtman:
GAN-Supervised Dense Visual Alignment. CVPR 2022: 13460-13471 - [c38]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 - [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]Chaowei Xiao, Jun-Yan Zhu, Bo Li, Warren He, Mingyan Liu, Dawn Song:
Spatially Transformed Adversarial Examples. ICLR (Poster) 2018 - [c15]Judy Hoffman, Eric Tzeng, Taesung Park, Jun-Yan Zhu, Phillip Isola, Kate Saenko, Alexei A. Efros, Trevor Darrell:
CyCADA: Cycle-Consistent Adversarial Domain Adaptation. ICML 2018: 1994-2003 - [c14]Chaowei Xiao, Bo Li, Jun-Yan Zhu, Warren He, Mingyan Liu, Dawn Song:
Generating Adversarial Examples with Adversarial Networks. IJCAI 2018: 3905-3911 - [c13]Jun-Yan Zhu, Zhoutong Zhang, Chengkai Zhang, Jiajun Wu, Antonio Torralba, Josh Tenenbaum, Bill Freeman:
Visual Object Networks: Image Generation with Disentangled 3D Representations. NeurIPS 2018: 118-129 - [c12]Ting-Chun Wang, Ming-Yu Liu, Jun-Yan Zhu, Nikolai Yakovenko, Andrew Tao, Jan Kautz, Bryan Catanzaro:
Video-to-Video Synthesis. NeurIPS 2018: 1152-1164 - [c11]Shunyu Yao, Tzu-Ming Harry Hsu, Jun-Yan Zhu, Jiajun Wu, Antonio Torralba, Bill Freeman, Josh Tenenbaum:
3D-Aware Scene Manipulation via Inverse Graphics. NeurIPS 2018: 1891-1902 - [i18]Chaowei Xiao, Bo Li, Jun-Yan Zhu, Warren He, Mingyan Liu, Dawn Song:
Generating Adversarial Examples with Adversarial Networks. CoRR abs/1801.02610 (2018) - [i17]Chaowei Xiao, Jun-Yan Zhu, Bo Li, Warren He, Mingyan Liu, Dawn Song:
Spatially Transformed Adversarial Examples. CoRR abs/1801.02612 (2018) - [i16]Ting-Chun Wang, Ming-Yu Liu, Jun-Yan Zhu, Guilin Liu, Andrew Tao, Jan Kautz, Bryan Catanzaro:
Video-to-Video Synthesis. CoRR abs/1808.06601 (2018) - [i15]Shunyu Yao, Tzu-Ming Harry Hsu, Jun-Yan Zhu, Jiajun Wu, Antonio Torralba, William T. Freeman, Joshua B. Tenenbaum:
3D-Aware Scene Manipulation via Inverse Graphics. CoRR abs/1808.09351 (2018) - [i14]Yunzhu Li, Jiajun Wu, Jun-Yan Zhu, Joshua B. Tenenbaum, Antonio Torralba, Russ Tedrake:
Propagation Networks for Model-Based Control Under Partial Observation. CoRR abs/1809.11169 (2018) - [i13]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. CoRR abs/1811.10597 (2018) - [i12]Tongzhou Wang, Jun-Yan Zhu, Antonio Torralba, Alexei A. Efros:
Dataset Distillation. CoRR abs/1811.10959 (2018) - [i11]Jun-Yan Zhu, Zhoutong Zhang, Chengkai Zhang, Jiajun Wu, Antonio Torralba, Joshua B. Tenenbaum, William T. Freeman:
Visual Object Networks: Image Generation with Disentangled 3D Representation. CoRR abs/1812.02725 (2018) - 2017
- [j6]Richard Zhang, Jun-Yan Zhu, Phillip Isola, Xinyang Geng, Angela S. Lin, Tianhe Yu, Alexei A. Efros:
Real-time user-guided image colorization with learned deep priors. ACM Trans. Graph. 36(4): 119:1-119:11 (2017) - [j5]Ting-Chun Wang, Jun-Yan Zhu, Nima Khademi Kalantari, Alexei A. Efros, Ravi Ramamoorthi:
Light field video capture using a learning-based hybrid imaging system. ACM Trans. Graph. 36(4): 133:1-133:13 (2017) - [c10]Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, Alexei A. Efros:
Image-to-Image Translation with Conditional Adversarial Networks. CVPR 2017: 5967-5976 - [c9]Jun-Yan Zhu, Taesung Park, Phillip Isola, Alexei A. Efros:
Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks. ICCV 2017: 2242-2251 - [c8]Jun-Yan Zhu, Richard Zhang, Deepak Pathak, Trevor Darrell, Alexei A. Efros, Oliver Wang, Eli Shechtman:
Toward Multimodal Image-to-Image Translation. NIPS 2017: 465-476 - [i10]Jun-Yan Zhu, Taesung Park, Phillip Isola, Alexei A. Efros:
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks. CoRR abs/1703.10593 (2017) - [i9]Ting-Chun Wang, Jun-Yan Zhu, Nima Khademi Kalantari, Alexei A. Efros, Ravi Ramamoorthi:
Light Field Video Capture Using a Learning-Based Hybrid Imaging System. CoRR abs/1705.02997 (2017) - [i8]Richard Zhang, Jun-Yan Zhu, Phillip Isola, Xinyang Geng, Angela S. Lin, Tianhe Yu, Alexei A. Efros:
Real-Time User-Guided Image Colorization with Learned Deep Priors. CoRR abs/1705.02999 (2017) - [i7]Judy Hoffman, Eric Tzeng, Taesung Park, Jun-Yan Zhu, Phillip Isola, Kate Saenko, Alexei A. Efros, Trevor Darrell:
CyCADA: Cycle-Consistent Adversarial Domain Adaptation. CoRR abs/1711.03213 (2017) - [i6]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. CoRR abs/1711.11585 (2017) - [i5]Jun-Yan Zhu, Richard Zhang, Deepak Pathak, Trevor Darrell, Alexei A. Efros, Oliver Wang, Eli Shechtman:
Toward Multimodal Image-to-Image Translation. CoRR abs/1711.11586 (2017) - 2016
- [c7]Ting-Chun Wang, Jun-Yan Zhu, Hiroaki Ebi, Manmohan Chandraker, Alexei A. Efros, Ravi Ramamoorthi:
A 4D Light-Field Dataset and CNN Architectures for Material Recognition. ECCV (3) 2016: 121-138 - [c6]Jun-Yan Zhu, Philipp Krähenbühl, Eli Shechtman, Alexei A. Efros:
Generative Visual Manipulation on the Natural Image Manifold. ECCV (5) 2016: 597-613 - [i4]Ting-Chun Wang, Jun-Yan Zhu, Hiroaki Ebi, Manmohan Chandraker, Alexei A. Efros, Ravi Ramamoorthi:
A 4D Light-Field Dataset and CNN Architectures for Material Recognition. CoRR abs/1608.06985 (2016) - [i3]Jun-Yan Zhu, Philipp Krähenbühl, Eli Shechtman, Alexei A. Efros:
Generative Visual Manipulation on the Natural Image Manifold. CoRR abs/1609.03552 (2016) - [i2]Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, Alexei A. Efros:
Image-to-Image Translation with Conditional Adversarial Networks. CoRR abs/1611.07004 (2016) - 2015
- [j4]Jun-Yan Zhu, Jiajun Wu, Yan Xu, Eric I-Chao Chang, Zhuowen Tu:
Unsupervised Object Class Discovery via Saliency-Guided Multiple Class Learning. IEEE Trans. Pattern Anal. Mach. Intell. 37(4): 862-875 (2015) - [c5]Jun-Yan Zhu, Philipp Krähenbühl, Eli Shechtman, Alexei A. Efros:
Learning a Discriminative Model for the Perception of Realism in Composite Images. ICCV 2015: 3943-3951 - [i1]Jun-Yan Zhu, Philipp Krähenbühl, Eli Shechtman, Alexei A. Efros:
Learning a Discriminative Model for the Perception of Realism in Composite Images. CoRR abs/1510.00477 (2015) - 2014
- [j3]Yan Xu, Jun-Yan Zhu, Eric I-Chao Chang, Maode Lai, Zhuowen Tu:
Weakly supervised histopathology cancer image segmentation and classification. Medical Image Anal. 18(3): 591-604 (2014) - [j2]Jun-Yan Zhu, Yong Jae Lee, Alexei A. Efros:
AverageExplorer: interactive exploration and alignment of visual data collections. ACM Trans. Graph. 33(4): 160:1-160:11 (2014) - [c4]Jiajun Wu, Yibiao Zhao, Jun-Yan Zhu, Siwei Luo, Zhuowen Tu:
MILCut: A Sweeping Line Multiple Instance Learning Paradigm for Interactive Image Segmentation. CVPR 2014: 256-263 - [c3]Kai Xu, Leonidas J. Guibas, Alexei A. Efros, Shi-Min Hu, Ariel Shamir, Jun-Yan Zhu:
Data-driven visual computing. SIGGRAPH ASIA Courses 2014: 7:1 - 2013
- [j1]Tao Chen, Jun-Yan Zhu, Ariel Shamir, Shi-Min Hu:
Motion-Aware Gradient Domain Video Composition. IEEE Trans. Image Process. 22(7): 2532-2544 (2013) - 2012
- [c2]Yan Xu, Jun-Yan Zhu, Eric I-Chao Chang, Zhuowen Tu:
Multiple clustered instance learning for histopathology cancer image classification, segmentation and clustering. CVPR 2012: 964-971 - [c1]Jun-Yan Zhu, Jiajun Wu, Yichen Wei, Eric I-Chao Chang, Zhuowen Tu:
Unsupervised object class discovery via saliency-guided multiple class learning. CVPR 2012: 3218-3225
Coauthor Index