Institution · Adobe Systems (United States)
Most cited papers from Adobe Systems (United States)
Adobe Systems (United States)
What are the most cited papers from Adobe Systems (United States)?
The most cited paper from Adobe Systems (United States) is "CBAM: Convolutional Block Attention Module" (Sanghyun Woo, Jongchan Park, Joon‐Young Lee et al., 2018), with 23,707 citations. Next come "The Unreasonable Effectiveness of Deep Features as a Perceptual Metric" (13,833) and "The No-U-turn sampler: adaptively setting path lengths in Hamiltonian Monte Carlo" (3,272).
Showing 50 of 60 papers. Every paper with more than 537 citations is listed.
| # | Paper | ||
|---|---|---|---|
| 1 | CBAM: Convolutional Block Attention Module Sanghyun Woo, Jongchan Park, Joon‐Young Lee et al. · Lecture notes in computer science | 2018 | 23,707 |
| 2 | The Unreasonable Effectiveness of Deep Features as a Perceptual Metric Richard Zhang, Phillip Isola, Alexei A. Efros et al. | Jun 2018 | 13,833 |
| 3 | The No-U-turn sampler: adaptively setting path lengths in Hamiltonian Monte Carlo Matthew D. Homan, Andrew Gelman · arXiv (Cornell University) | 2014 | 3,272 |
| 4 | PatchMatch Connelly Barnes, Eli Shechtman, Adam Finkelstein et al. · ACM Transactions on Graphics | 27 Jul 2009 | 3,005 |
| 5 | Generative Image Inpainting with Contextual Attention Jiahui Yu, Zhe Lin, Jimei Yang et al. | Jun 2018 | 2,537 |
| 6 | Semantic contours from inverse detectors Bharath Hariharan, Pablo Arbeláez, Lubomir Bourdev et al. | Nov 2011 | 1,780 |
| 7 | Image Captioning with Semantic Attention Quanzeng You, Hailin Jin, Zhaowen Wang et al. | Jun 2016 | 1,747 |
| 8 | Stochastic variational inference Matthew D. Hoffman, David M. Blei, Chong Wang et al. · Journal of Machine Learning Research | 2013 | 1,475 |
| 9 | A convolutional neural network cascade for face detection Haoxiang Li, Zhe Lin, Xiaohui Shen et al. | Jun 2015 | 1,434 |
| 10 | High-quality motion deblurring from a single image Qi Shan, Jiaya Jia, Aseem Agarwala · ACM Transactions on Graphics | Aug 2008 | 1,416 |
| 11 | Contrastive Learning for Unpaired Image-to-Image Translation Taesung Park, Alexei A. Efros, Richard Zhang et al. · Lecture notes in computer science | 2020 | 1,396 |
| 12 | A scalable active framework for region annotation in 3D shape collections Li Yi, Vladimir Grigoryevich Kim, Duygu Ceylan et al. · ACM Transactions on Graphics | 11 Nov 2016 | 1,320 |
| 13 | Label Consistent K-SVD: Learning a Discriminative Dictionary for Recognition Zhuolin Jiang, Zhe Lin, L.S. Davis · IEEE Transactions on Pattern Analysis and Machine Intelligence | 15 May 2013 | 1,260 |
| 14 | On the Continuity of Rotation Representations in Neural Networks Yi Zhou, Connelly Barnes, Jingwan Lu et al. | Jun 2019 | 1,205 |
| 15 | Generative Visual Manipulation on the Natural Image Manifold Jun-Yan Zhu, Philipp Krähenbühl, Eli Shechtman et al. · Lecture notes in computer science | 2016 | 1,175 |
| 16 | Image De-Raining Using a Conditional Generative Adversarial Network He Zhang, Vishwanath A. Sindagi, Vishal M. Patel · IEEE Transactions on Circuits and Systems for Video Technology | 3 Jun 2019 | 1,173 |
| 17 | TensoRF: Tensorial Radiance Fields Anpei Chen, Zexiang Xu, Andreas Geiger et al. · Lecture notes in computer science | 2022 | 1,168 |
| 18 | 3DMatch: Learning Local Geometric Descriptors from RGB-D Reconstructions Andy Zeng, Shuran Song, Matthias Nießner et al. | Jul 2017 | 1,163 |
| 19 | CNN-Generated Images Are Surprisingly Easy to Spot… for Now Sheng-Yu Wang, Oliver Wang, Richard Zhang et al. | Jun 2020 | 1,120 |
| 20 | In defense of Nearest-Neighbor based image classification Oren Boiman, Eli Shechtman, Michal Irani | Jun 2008 | 1,075 |
| 21 | Poselets: Body part detectors trained using 3D human pose annotations Lubomir Bourdev, Jitendra Malik | Sep 2009 | 1,008 |
| 22 | A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors Rick Szeliski, Ramin Zabih, Daniel Scharstein et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence | 23 Apr 2008 | 983 |
| 23 | Interactive Facial Feature Localization Vuong Le, Jonathan Brandt, Zhe Lin et al. · Lecture notes in computer science | 2012 | 975 |
| 24 | High-Resolution Image Inpainting Using Multi-scale Neural Patch Synthesis Chao Yang, Xin Lu, Zhe Lin et al. | Jul 2017 | 923 |
| 25 | Halide Jonathan Ragan‐Kelley, Connelly Barnes, Andrew B. Adams et al. | 11 Jun 2013 | 910 |
| 26 | MAttNet: Modular Attention Network for Referring Expression Comprehension Licheng Yu, Zhe Lin, Xiaohui Shen et al. | Jun 2018 | 874 |
| 27 | NISP: Pruning Networks Using Neuron Importance Score Propagation Ruichi Yu, Ang Li, Chun-Fu Chen et al. | Jun 2018 | 854 |
| 28 | Coupled Dictionary Training for Image Super-Resolution Jianchao Yang, Zhaowen Wang, Zhe Lin et al. · IEEE Transactions on Image Processing | 11 Apr 2012 | 821 |
| 29 | MVSNeRF: Fast Generalizable Radiance Field Reconstruction from Multi-View Stereo Anpei Chen, Zexiang Xu, Fuqiang Zhao et al. · 2021 IEEE/CVF International Conference on Computer Vision (ICCV) | Oct 2021 | 788 |
| 30 | Learning Rich Features for Image Manipulation Detection Peng Zhou, Xintong Han, Vlad I. Morariu et al. | Jun 2018 | 762 |
| 31 | Improved seam carving for video retargeting Michael Rubinstein, Ariel Shamir, Shai Avidan · ACM Transactions on Graphics | Aug 2008 | 748 |
| 32 | Learning a discriminative dictionary for sparse coding via label consistent K-SVD Zhuolin Jiang, Zhe Lin, Larry Steven Davis | Jun 2011 | 746 |
| 33 | Toward Multimodal Image-to-Image Translation Jun-Yan Zhu, Richard Zhang, Deepak Pathak et al. · arXiv (Cornell University) | 30 Nov 2017 | 740 |
| 34 | Art and the science of generative AI Ziv Epstein, Aaron Hertzmann, the Investigators of Human Creativity et al. · Science | 15 Jun 2023 | 735 |
| 35 | Top-Down Neural Attention by Excitation Backprop Jianming Zhang, Sarah Adel Bargal, Zhe Lin et al. · International Journal of Computer Vision | 23 Dec 2017 | 723 |
| 36 | MedCLIP: Contrastive Learning from Unpaired Medical Images and Text Zifeng Wang, Zhenbang Wu, Dinesh Chandra Agarwal et al. | 2022 | 713 |
| 37 | Attribute2Image: Conditional Image Generation from Visual Attributes Xinchen Yan, Jimei Yang, Kihyuk Sohn et al. · Lecture notes in computer science | 2016 | 708 |
| 38 | Deep Photo Style Transfer Fujun Luan, Sylvain Paris, Eli Shechtman et al. | Jul 2017 | 686 |
| 39 | Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes Zhengqi Li, Simon Niklaus, Noah Snavely et al. | Jun 2021 | 683 |
| 40 | Bias and Fairness in Large Language Models: A Survey Isabel O. Gallegos, Ryan A. Rossi, Joe Barrow et al. · Computational Linguistics | 2024 | 656 |
| 41 | Articulated mesh animation from multi-view silhouettes Daniel Vlasic, Ilya Baran, Wojciech Matusik et al. · ACM Transactions on Graphics | Aug 2008 | 638 |
| 42 | Summarizing visual data using bidirectional similarity Denis Simakov, Yaron Caspi, Eli Shechtman et al. | Jun 2008 | 633 |
| 43 | Multi-Concept Customization of Text-to-Image Diffusion Nupur Kumari, Bingliang Zhang, Richard Zhang et al. | Jun 2023 | 623 |
| 44 | YouTube-VOS: Sequence-to-Sequence Video Object Segmentation Ning Xu, Linjie Yang, Yuchen Fan et al. · Lecture notes in computer science | 2018 | 619 |
| 45 | STC: A Simple to Complex Framework for Weakly-Supervised Semantic Segmentation Yunchao Wei, Xiaodan Liang, Yunpeng Chen et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence | 6 Dec 2016 | 619 |
| 46 | Generative Face Completion Yijun Li, Sifei Liu, Jimei Yang et al. | Jul 2017 | 618 |
| 47 | Investigating Haze-Relevant Features in a Learning Framework for Image Dehazing Ketan Tang, Jianchao Yang, Jue Wang | Jun 2014 | 616 |
| 48 | Real-time hand-tracking with a color glove Robert Y. Wang, Jovan Popović · ACM Transactions on Graphics | 27 Jul 2009 | 612 |
| 49 | Deep Video Deblurring for Hand-Held Cameras Shuochen Su, Mauricio Delbracio, Jue Wang et al. | Jul 2017 | 609 |
| 50 | Bilateral Filtering: Theory and Applications Sylvain Paris, Pierre Kornprobst, Jack Tumblin et al. · Foundations and Trends® in Computer Graphics and Vision | 20 Aug 2009 | 585 |
Citations are OpenAlex's own counts, from its 2026-09-23 snapshot, so the ranking can differ from Google Scholar or Web of Science. A paper is listed for an institution when any of its authors gave it as an affiliation; retracted papers and papers whose citation count cannot be traced to citing works are left out, and a preprint and the article it became are shown once. Release dates are OpenAlex's: where a source gave only a month or a year, that is what is shown. How the lists are chosen.