Fetching the paper…
Reading the bibliography…
Adapting a segmentation model from a labeled source domain to a target domain, where a single unlabeled datum is available, is one the most challenging problems in domain adaptation and is otherwise known as one-shot unsupervised domain adaptation (OSUDA).
Unbiased look at dataset bias
Antonio Torralba and Alexei A Efros · 2011
Earlier work this paper cites.
U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
Earlier work this paper cites.
Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
Earlier work this paper cites.
The cityscapes dataset for semantic urban scene understanding
Marius Cordts, Mohamed Omran, Sebastian Ramos, Timo Rehfeld, Markus Enzweiler, Rodrigo Benenson, Uwe Franke, Stefan Roth, and Bernt Schiele · 2016
Earlier work this paper cites.
A neural algorithm of artistic style
Leon A Gatys, Alexander S Ecker, and Matthias Bethge · 2016
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Fcns in the wild: Pixel-level adversarial and constraint-based adaptation
Judy Hoffman, Dequan Wang, Fisher Yu, and Trevor Darrell · 2016
Earlier work this paper cites.
Playing for data: Ground truth from computer games
Stephan R Richter, Vibhav Vineet, Stefan Roth, and Vladlen Koltun · 2016
Earlier work this paper cites.
The synthia dataset: A large collection of synthetic images for semantic segmentation of urban scenes
German Ros, Laura Sellart, Joanna Materzynska, David Vazquez, and Antonio M Lopez · 2016
Earlier work this paper cites.
Importance-aware semantic segmentation for autonomous driving system
Bi-ke Chen, Chen Gong, and Jian Yang · 2017
Earlier work this paper cites.
Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs
Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L Yuille · 2017
Earlier work this paper cites.
Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
Earlier work this paper cites.
Arbitrary style transfer in real-time with adaptive instance normalization
Xun Huang and Serge Belongie · 2017
Earlier work this paper cites.
Few-shot adversarial domain adaptation
Saeid Motiian, Quinn Jones, Seyed Iranmanesh, and Gianfranco Doretto · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
Unpaired image-to-image translation using cycle-consistent adversarial networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A Efros · 2017
Earlier work this paper cites.
One-shot unsupervised cross domain translation
Sagie Benaim and Lior Wolf · 2018
Earlier work this paper cites.
A domain-adaptive two-stream u-net for electron microscopy image segmentation
Róger Bermúdez-Chacón, Pablo Márquez-Neila, Mathieu Salzmann, and Pascal Fua · 2018
Earlier work this paper cites.
Coco-stuff: Thing and stuff classes in context
Holger Caesar, Jasper Uijlings, and Vittorio Ferrari · 2018
Earlier work this paper cites.
Few-shot semantic segmentation with prototype learning
Nanqing Dong and Eric P Xing · 2018
Earlier work this paper cites.
Cycada: Cycle-consistent adversarial domain adaptation
Judy Hoffman, Eric Tzeng, Taesung Park, Jun-Yan Zhu, Phillip Isola, Kate Saenko, Alexei Efros, and Trevor Darrell · 2018
Earlier work this paper cites.
Domain transfer through deep activation matching
Haoshuo Huang, Qixing Huang, and Philipp Krahenbuhl · 2018
Earlier work this paper cites.
Learning to adapt structured output space for semantic segmentation
Yi-Hsuan Tsai, Wei-Chih Hung, Samuel Schulter, Kihyuk Sohn, Ming-Hsuan Yang, and Manmohan Chandraker · 2018
Cited alongside, same era.
Unsupervised domain adaptation for semantic segmentation via class-balanced self-training
Yang Zou, Zhiding Yu, BVK Kumar, and Jinsong Wang · 2018
Cited alongside, same era.
Bidirectional learning for domain adaptation of semantic segmentation
Yunsheng Li, Lu Yuan, and Nuno Vasconcelos · 2019
Cited alongside, same era.
Taking a closer look at domain shift: Category-level adversaries for semantics consistent domain adaptation
Yawei Luo, Liang Zheng, Tao Guan, Junqing Yu, and Yi Yang · 2019
Cited alongside, same era.
Tong Shen, Dong Gong, Wei Zhang, Chunhua Shen, and Tao Mei · 2019
Cited alongside, same era.
Senay Cakir, Marcel Gauß, Kai Häppeler, Yassine Ounajjar, Fabian Heinle, and Reiner Marchthaler · 2022
Later among the works it cites.
Mpaf: Model poisoning attacks to federated learning based on fake clients
Xiaoyu Cao and Neil Zhenqiang Gong · 2022
Later among the works it cites.
Semantic image segmentation: Two decades of research
Gabriela Csurka, Riccardo Volpi, Boris Chidlovskii, et al · 2022
Later among the works it cites.
Frido: Feature pyramid diffusion for complex scene image synthesis
Wan-Cyuan Fan, Yen-Chun Chen, DongDong Chen, Yu Cheng, Lu Yuan, and Yu-Chiang Frank Wang · 2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Domain adaptation for structured output via discriminative patch representations
Yi-Hsuan Tsai, Kihyuk Sohn, Samuel Schulter, and Manmohan Chandraker · 2019
Cited alongside, same era.
Advent: Adversarial entropy minimization for domain adaptation in semantic segmentation
Tuan-Hung Vu, Himalaya Jain, Maxime Bucher, Matthieu Cord, and Patrick Pérez · 2019
Cited alongside, same era.
Few-shot adaptive faster r-cnn
Tao Wang, Xiaopeng Zhang, Li Yuan, and Jiashi Feng · 2019
Cited alongside, same era.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Cited alongside, same era.
Adversarial style mining for one-shot unsupervised domain adaptation
Yawei Luo, Ping Liu, Tao Guan, Junqing Yu, and Yi Yang · 2020
Cited alongside, same era.
Unsupervised intra-domain adaptation for semantic segmentation through self-supervision
Fei Pan, Inkyu Shin, Francois Rameau, Seokju Lee, and In So Kweon · 2020
Cited alongside, same era.
Unsupervised domain adaptation for mobile semantic segmentation based on cycle consistency and feature alignment
Marco Toldo, Umberto Michieli, Gianluca Agresti, and Pietro Zanuttigh · 2020
Cited alongside, same era.
Rui Gong, Qin Wang, Dengxin Dai, and Luc Van Gool · 2022
Later among the works it cites.
Daformer: Improving network architectures and training strategies for domain-adaptive semantic segmentation
Lukas Hoyer, Dengxin Dai, and Luc Van Gool · 2022
Later among the works it cites.
Hrda: Context-aware high-resolution domain-adaptive semantic segmentation
Lukas Hoyer, Dengxin Dai, and Luc Van Gool · 2022
Later among the works it cites.
Semantic scene segmentation for robotics
Juana Valeria Hurtado and Abhinav Valada · 2022
Later among the works it cites.
Compositional visual generation with composable diffusion models
Nan Liu, Shuang Li, Yilun Du, Antonio Torralba, and Joshua B Tenenbaum · 2022
Later among the works it cites.
Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
Later among the works it cites.
High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Later among the works it cites.
Photorealistic text-to-image diffusion models with deep language understanding
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, et al · 2022
Later among the works it cites.
Diffusers: State-of-the-art diffusion models
Patrick von Platen, Suraj Patil, Anton Lozhkov, Pedro Cuenca, Nathan Lambert, Kashif Rasul, Mishig Davaadorj, and Thomas Wolf · 2022
Later among the works it cites.
Style mixing and patchwise prototypical matching for one-shot unsupervised domain adaptive semantic segmentation
Xinyi Wu, Zhenyao Wu, Yuhang Lu, Lili Ju, and Song Wang · 2022
Later among the works it cites.
Mohamed Akrout, Bálint Gyepesi, Péter Holló, Adrienn Poór, Blága Kincső, Stephen Solis, Katrina Cirone, Jeremy Kawahara, Dekker Slade, Latif Abid, et al · 2023
Closest in time.
An image is worth one word: Personalizing text-to-image generation using textual inversion
Rinon Gal, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit H Bermano, Gal Chechik, and Daniel Cohen-Or · 2023
Closest in time.
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 · 2023
Closest in time.
Compvis/stable-diffusion-v1-4
Robin Rombach and Patrick Esser · 2023
Closest in time.
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
Closest in time.
Fake it till you make it: Learning (s) from a synthetic imagenet clone
Mert Bulent Sariyildiz, Karteek Alahari, Diane Larlus, and Yannis Kalantidis · 2023
Closest in time.
Adding conditional control to text-to-image diffusion models
Lvmin Zhang and Maneesh Agrawala · 2023
Closest in time.