This repo houses summaries for various excitng works in the field of Deep Learning. You can contribute summaries of your own. Check out our contributing guide to start contributing. Happy Reading & Summarizing!
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- Chung Min Kim, Mingxuan Wu, Justin Kerr, Ken Goldberg, Matthew Tancik, Angjoo Kanazawa, CVPR 2024
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- Luke Bailey,Euan Ong,Stuart Russel,Scott Emmons, ICML 2024
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- Ryan Greenblatt,Buck Shlegeris,Kshitij Sachan,Fabien Roger, ICML 2024
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- Zhiqiu Lin, Deepak Pathak, Baiqi Li, Jiayao Li, Xide Xia, Graham Neubig, Pengchuan Zhang, Deva Ramanan, ECCV 2024
- Zhiqiu Lin, Deepak Pathak, Baiqi Li, Jiayao Li, Xide Xia, Graham Neubig, Pengchuan Zhang, Deva Ramanan, ECCV 2024
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- Sachin Goyal, Ziwei Ji, Ankit Rawat, Aditya Menon, Sanjiv Kumar, Vaishnavh Nagarajan, ICLR 2024
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- Alexandre Ramé, Nino Vieillard, Léonard Hussenot, Robert Dadashi, Geoffrey Cideron, Olivier Bachem, Johan Ferret, ICML May 2024
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- Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Josh Susskind & Navdeep Jaitly, ICLR 2024
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INSTRUCTSCENE: INSTRUCTION-DRIVEN 3D INDOOR SCENE SYNTHESIS WITH SEMANTIC GRAPH PRIOR [Paper][Review]
- Chenguo Lin & Yadong Mu, ICLR 2024
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- Nupur Kumari, Bingliang Zhang, Sheng-Yu Wang, Eli Shechtman, Richard Zhang, Jun-Yan Zhu, ICCV 2023
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- Zhendong Wang, Jianmin Bao, Wengang Zhou, Weilun Wang, Hezhen Hu, Hong Chen, Houqiang Li, ICCV 2023
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DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation [Paper][Review]
- Nataniel Ruiz, Yuanzhen Li,Varun Jampani,Yael Pritch,Michael Rubinstein, Kfir Aberman, CVPR 2023
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- Nupur Kumari,Bingliang Zhang,Richard Zhang,Eli Shechtman & Jun-Yan Zhu, CVPR 2023
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- Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xao, Spencer Whitehead, Alexander C. Berg, Wan-Yen Lo, Piotr Dollar, Ross Girshick, ICCV 2023
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- Agrim Gupta, Jiajun Wu, Jia Deng, Li Fei-Fei, NIPS 2023
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An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion [Paper][Review]
- Rinon Gal1, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit H. Bermano, Gal Chechik, Daniel Cohen-Or, ICVR 2023
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Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video Generation [Paper][Review]
- Jay Zhangjie Wu, Yixiao Ge, Xintao Wang, Stan Weixian Lei, Yuchao Gu, Wynne Hsu, Ying Shan, Xiaohu Qie, Mike Zheng Shou, ICCV 2023
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- Andy Zou, Zifan Wang, Nicholas Carlini , Milad Nasr, J. Zico Kolter & Matt Fredrikson
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What do Neural Networks Learn in Image Classification? A Frequency Shortcut Perspective [Paper][Review]
- Shunxin Wang, Raymond Veldhuis ,Christoph Brune ,Nicola Strisciuglio, ICCV 2023
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GAN-based image steganography for enhancing security via adversarial attack and pixel-wise deep fusion [Paper][Review ]
- Chao Yuan, Hongxia Wang, Peisong He, Jie Luo, Bin Li, Springer Multimedia tools and applications 2022
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Human-level play in the game of Diplomacy by combining language models with strategic reasoning [Paper][Review]
- Meta Fundamental AI Research Diplomacy Team (FAIR), Antin Bakhtun, Noam Brown, Emily Dinan, Science Journal 2022
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- Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S. Sara Mahdavi, Rapha Gontijo Lopes, Tim Salimans, Jonathan Ho, David J Fleet, Mohammad Norouzi, NIPS 2022
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- Yue Zhao, Ishan Misra, Philipp Krähenbüh, Rohit Girdhar, Facebook AI Research- Meta AI, University of Texas, Austin
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- Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, Ilya Sutskever , ICML 2021
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- Alexey Dosovitsky, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, Neil Houlsby, ICLR 2021
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w2v-BERT: Combining Contrastive Learning and Masked Language Modelling for Self-Supervised Speech Pre-Training [Paper][Review]
- Yu-An Chung, Yu Zhang, Wei Han, Chung-Cheng Chiu, James Qin, Ruoming Pang, Yonghui Wu
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- Jihwan Bang, Heesu Kim, YoungJoon Yoo, Jung-Woo Ha, Jonghyun Choi, CVPR 2021
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- Tianwei Yin, Xingyi Zhou, Philipp Krahenbuhl (UT Austin), CVPR 2021
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- Zekun Hao, Arun Mallya, Serge Belongie, Ming-Yu Liu, ICCV 2021
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- Michael Niemeyer, Andreas Geiger, CVPR 2021
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- Songwei Ge, Devi Parikh, Vedanuj Goswami & C. Lawrence Zitnick, ICLR 2021
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- Abhishek Badki, Orazio Gallo, Jan Kautz, Pradeep Sen, CVPR 2021
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- Katja Schwarz, Yiyi Liao, Andreas Geiger, NeurIPS 2021
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BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension [Paper][Review]
- Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, Luke Zettlemoyer, ACL 2020
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- Lucas Bourtoule, Varun Chandrasekaran, Christopher A. Choquette-Choo, Hengrui Jia,Adelin Travers, Baiwu Zhang, David Lie,Nicolas Papernot, IEEE 2020
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- Manzil Zaheer, Guru Guruganesh, Avinava Dubey, Joshua Ainslie, Chris Alberti, Santiago Ontanon, Philip Pham, Anirudh Ravula, Qifan Wang, Li Yang, Amr Ahmed, NeurIPS 2020
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- Qin, Xu and Wang, Zhilin and Bai, Yuanchao and Xie, Xiaodong and Jia, Huizhu, AAAI_2020
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Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild [Paper][Review]
- Shangzhe Wu, Christian Rupprecht, Andrea Vedaldi, CVPR 2020
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- Alexey Dosovitskiy, Josip Djolonga, ICLR 2020
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- Sean Bell, Yiqun Liu, Sami Alsheikh, Yina Tang, Ed Pizzi, M. Henning, Karun Singh, Omkar Parkhi, Fedor Borisyuk, KDD 2020
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- Zhen Zhu, Zhiliang Xu, Ansheng You, Xiang Bai, CVPR 2020
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- Seung Wook Kim, Yuhao Zhou, Jonah Philion, Antonio Torralba, Sanja Fidler, CVPR 2020
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- Adam Gleave, Michael Dennis, Cody Wild, Neel Kant, Sergey Levine, Stuart Russell, ICLR 2020
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- Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre H. Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, Bilal Piot, Koray Kavukcuoglu, Rémi Munos, Michal Valko, CVPR 2020
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ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks [Paper][Review]
- Jiasen Lu, Dhruv Batra, Devi Parikh, Stefan Lee, NIPS 2019
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- Prajit Ramachandran, Niki Parmar, Ashish Vaswani, Irwan Bello, Anselm Levskaya, Jonathon Shlens, NIPS 2019
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- Lajanugen Logeswaran , Ming-Wei Chang‡ Kenton Lee , Kristina Toutanova , Jacob Devlin, Honglak Lee ACL-2019
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Do you know that Florence is packed with visitors? Evaluating state-of-the-art models of speaker commitment [Paper][Review]
- Nanjiang Jiang and Marie-Catherine de Marneffe , ACL-2019
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Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations [Paper][Review]
- Vincent Sitzmann, Michael Zollhofer, Gordon Wetzstein, NIPS-2019
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- Rui Xia, Zixiang Ding, ACL-2019
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- Sindy Lowe, Peter O' Connor, Bastiaan S. Veeling, NIPS-2019
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- Wen Zhang, Yang Feng, Fandong Meng, Di You, Qun Liu, ACL-2019
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- John Hewitt, Percy Liang, EMNLP-2019
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- Xiang Lisa Li, Jason Eisner, EMNLP-2019
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vGraph: A Generative Model for Joint Community Detection and Node Representational Learning [Paper][Review]
- Fan-Yun Sun, Meng Qu, Jordan Hoffmann, Chin-Wei Huang, Jian Tang, NIPS-2019
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- Vaishnavh Nagarajan, J. Zico Kolter, NIPS-2019
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- Tamar Rott Shaham, Tali Dekel, Tomer Michaeli, ICCV-2019
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- Hongyang Gao, Shuiwang Ji, ICML-2019
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- Cihang Xie, Yuxin Wu, Laurens van der Maaten, Alan Yuille, kaiming He, CVPR-2019
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- Chaofan Chen, Oscar Li, Chaofan Tao, Alina Jade Barnett, Jonathan Su, Cynthia Rudin, NIPS-2019
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- Deniz Engin, Anil Genc, Hazim Kemal Ekenel, CVPR 2018
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- Tero Karras, Samuli Laine, Timo Aila, IEEE_CVPR_2018
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- Judy Hoffman, Eric Tzeng, Taesung Park, Jun-Yan Zhu, Phillip Isola, Kate Saenko, Alexei A. Efros, Trevor Darrell, ICML-2018
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- Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, Illia Polosukhin, NeurIPS 2017
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- Jun-Yan Zhu, Taesung Park, Phillip Isola, Alexei A. Efros, ICCV-2017
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- Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger, CVPR-2017
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- Chuan Guo, Geoff Pleiss, Yu Sun, Kilian Q. Weinberger, ICML-2017
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- Jonas Mueller, Aditya Thyagarajan, AAAI-2016
We appreciate all contributions to the set of summaries. Please refer to CONTRIBUTING.md for the contributing guideline.
papers_we_read is an open source repository that welcomes any contribution and feedback. We wish the collected sets of summaries can help the DL community to start with the practice of reading and understanding research papers which is a potent skill in the research community. Most of our contributors include students enrolled in undergraduate programmes. We are grateful for all the contributions that help improve this collection of summaries.
This repo is open-sourced under the MIT License.