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Recently diffusion models have shown improvement in synthetic image quality as well as better control in generation.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, K. Li, and Li Fei-Fei · 2009
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Faster r-cnn: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross B. Girshick, and Jian Sun · 2015
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Cut, paste and learn: Surprisingly easy synthesis for instance detection
Debidatta Dwibedi, Ishan Misra, and Martial Hebert · 2017
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Synthesizing training data for object detection in indoor scenes
Georgios Georgakis, Arsalan Mousavian, Alexander C Berg, and Jana Kosecka · 2017
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Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross B. Girshick · 2017
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Object detection using deep cnns trained on synthetic images
Param S. Rajpura, Ravi Sadananda Hegde, and Hristo Bojinov · 2017
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Modeling visual context is key to augmenting object detection datasets
Nikita Dvornik, Julien Mairal, and Cordelia Schmid · 2018
Earlier work this paper cites.
Training deep networks with synthetic data: Bridging the reality gap by domain randomization
Jonathan Tremblay, Aayush Prakash, David Acuna, Mark Brophy, V. Jampani, Cem Anil, Thang To, Eric Cameracci, Shaad Boochoon, and Stan Birchfield · 2018
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Instaboost: Boosting instance segmentation via probability map guided copy-pasting
Haoshu Fang, Jianhua Sun, Runzhong Wang, Minghao Gou, Yong-Lu Li, and Cewu Lu · 2019
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Lvis: A dataset for large vocabulary instance segmentation
Agrim Gupta, Piotr Dollar, and Ross Girshick · 2019
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Detectron2
Yuxin Wu, Alexander Kirillov, Francisco Massa, Wan-Yen Lo, and Ross Girshick · 2019
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U2-net: Going deeper with nested u-structure for salient object detection
Xuebin Qin, Zichen Zhang, Chenyang Huang, Masood Dehghan, Osmar Zaiane, and Martin Jagersand · 2020
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Simple copy-paste is a strong data augmentation method for instance segmentation
Golnaz Ghiasi, Yin Cui, Aravind Srinivas, Rui Qian, Tsung-Yi Lin, Ekin D Cubuk, Quoc V Le, and Barret Zoph · 2021
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Lora: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen · 2021
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Sdedit: Guided image synthesis and editing with stochastic differential equations
Chenlin Meng, Yutong He, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, and Stefano Ermon · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
Cited alongside, same era.
Zero-shot text-to-image generation
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever · 2021
Cited alongside, same era.
Probabilistic two-stage detection
Xingyi Zhou, Vladlen Koltun, and Philipp Krähenbühl · 2021
Cited alongside, same era.
Peekaboo: Text to image diffusion models are zero-shot segmentors
Ryan Burgert, Kanchana Ranasinghe, Xiang Li, and Michael S Ryoo · 2022
Cited alongside, same era.
Is synthetic data from generative models ready for image recognition?
Ruifei He, Shuyang Sun, Xin Yu, Chuhui Xue, Wenqing Zhang, Philip Torr, Song Bai, and Xiaojuan Qi · 2022
Text-to-image diffusion models are zero-shot classifiers
Kevin Clark and Priyank Jaini · 2023
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Feedback-guided data synthesis for imbalanced classification
Reyhane Askari Hemmat, Mohammad Pezeshki, Florian Bordes, Michal Drozdzal, and Adriana Romero-Soriano · 2023
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Text2room: Extracting textured 3d meshes from 2d text-to-image models
Lukas Höllein, Ang Cao, Andrew Owens, Justin Johnson, and Matthias Nießner · 2023
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Explore the power of synthetic data on few-shot object detection
Shaobo Lin, Kun Wang, Xingyu Zeng, and Rui Zhao · 2023
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Diffusion hyperfeatures: Searching through time and space for semantic correspondence
Grace Luo, Lisa Dunlap, Dong Huk Park, Aleksander Holynski, and Trevor Darrell · 2023
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Cited alongside, same era.
Image segmentation using text and image prompts
Timo Lüddecke and Alexander Ecker · 2022
Cited alongside, same era.
Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
Cited alongside, same era.
High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Cited alongside, same era.
Palette: Image-to-image diffusion models
Chitwan Saharia, William Chan, Huiwen Chang, Chris Lee, Jonathan Ho, Tim Salimans, David Fleet, and Mohammad Norouzi · 2022
Cited alongside, same era.
A unified transformer framework for group-based segmentation: Co-segmentation, co-saliency detection and video salient object detection, 2022
Yukun Su, Jingliang Deng, Ruizhou Sun, Guosheng Lin, and Qingyao Wu · 2022
Cited alongside, same era.
Scaling autoregressive models for content-rich text-to-image generation
Jiahui Yu, Yuanzhong Xu, Jing Yu Koh, Thang Luong, Gunjan Baid, Zirui Wang, Vijay Vasudevan, Alexander Ku, Yinfei Yang, Burcu Karagol Ayan, et al · 2022
Cited alongside, same era.
Selfreformer: Self-refined network with transformer for salient object detection
Yi Ke Yun and Weisi Lin · 2022
Cited alongside, same era.
Closest in time.
Diffusion models beat gans on image classification
Soumik Mukhopadhyay, Matthew Gwilliam, Vatsal Agarwal, Namitha Padmanabhan, Archana Swaminathan, Srinidhi Hegde, Tianyi Zhou, and Abhinav Shrivastava · 2023
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Localizing object-level shape variations with text-to-image diffusion models
Or Patashnik, Daniel Garibi, Idan Azuri, Hadar Averbuch-Elor, and Daniel Cohen-Or · 2023
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Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation
Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Yael Pritch, Michael Rubinstein, and Kfir Aberman · 2023
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Fake it till you make it: Learning transferable representations from synthetic imagenet clones
Mert Bulent Sariyildiz, Karteek Alahari, Diane Larlus, and Yannis Kalantidis · 2023
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Emergent correspondence from image diffusion
Luming Tang, Menglin Jia, Qianqian Wang, Cheng Perng Phoo, and Bharath Hariharan · 2023
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Stablerep: Synthetic images from text-to-image models make strong visual representation learners
Yonglong Tian, Lijie Fan, Phillip Isola, Huiwen Chang, and Dilip Krishnan · 2023
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Sketch-guided text-to-image diffusion models
Andrey Voynov, Kfir Aberman, and Daniel Cohen-Or · 2023
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Denoising diffusion autoencoders are unified self-supervised learners
Weilai Xiang, Hongyu Yang, Di Huang, and Yunhong Wang · 2023
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Adding conditional control to text-to-image diffusion models
Lvmin Zhang, Anyi Rao, and Maneesh Agrawala · 2023
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X-paste: Revisiting scalable copy-paste for instance segmentation using clip and stablediffusion
Hanqing Zhao, Dianmo Sheng, Jianmin Bao, Dongdong Chen, Dong Chen, Fang Wen, Lu Yuan, Ce Liu, Wenbo Zhou, Qi Chu, et al · 2023
Closest in time.