Images Speak in Images: A Generalist Painter for In-Context Visual Learning
Xinlong Wang, Wen Wang, Yue Cao, Chunhua Shen, Tiejun Huang
摘要
Task prompts Paintings Input images Figure 1. An illustration of the in-context inference of Painter. Painter is a generalist vision model, which can automatically perform vision tasks according to the input task prompts without the task specific heads. Painter can not only perform in-domain tasks with highly competitive performance, such as semantic segmentation (Row 1), instance segmentation (Row 2), depth estimation (Row 3), keypoint detection (Row 4), denoising (Row 5), deraining (Row 6), and image enhancement (Row7), but also be able to rapidly adapt to various out-of-domain vision tasks using simple prompts, such as open-category object segmentation, keypoint detection, and instance segmentation (Row 8-10).
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper133
- Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale PredictionKeyu Tian, Yi Jiang, Zehuan Yuan, Bingyue Peng 等NeurIPS 2024 · 被引用 1,199 次
- Segment Everything Everywhere All at OnceXueyan Zou, Jianwei Yang, Hao Zhang, Feng Li 等NeurIPS 2023 · 被引用 889 次
- VisionLLM: Large Language Model is also an Open-Ended Decoder for Vision-Centric TasksWenhai Wang, Zhe Chen, Xiaokang Chen, Jiannan Wu 等NeurIPS 2023 · 被引用 725 次
- A Survey on In-context LearningQingxiu Dong, Lei Li, Damai Dai, Ce Zheng 等EMNLP 2024 · 被引用 479 次
- An Embodied Generalist Agent in 3D WorldJiangyong Huang, Silong Yong, Xiaojian Ma, Xiongkun Linghu 等ICML 2024 · 被引用 361 次
它引用的顶会 Paper20
- Language Models are Few-Shot LearnersTom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah 等NeurIPS 2020 · 被引用 64,255 次
- Swin Transformer: Hierarchical Vision Transformer using Shifted WindowsZe Liu, Yutong Lin, Yue Cao, Han Hu 等ICCV 2021 · 被引用 31,683 次
- An Image is Worth 16x16 Words: Transformers for Image Recognition at ScaleAlexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn 等ICLR 2021 · 被引用 21,477 次
- Flamingo: a Visual Language Model for Few-Shot LearningJean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, Antoine Miech 等NeurIPS 2022 · 被引用 6,707 次
- Uformer: A General U-Shaped Transformer for Image RestorationZhendong Wang, Xiaodong Cun, Jianmin Bao, Wengang Zhou 等CVPR 2022 · 被引用 1,970 次
相关 Paper
- Test-Time Visual In-Context TuningJiahao Xie, Alessio Tonioni, Nathalie Rauschmayr, Federico Tombari 等CVPR 2025
- SegGPT: Towards Segmenting Everything In ContextXinlong Wang, Xiaosong Zhang, Yue Cao, Wen Wang 等ICCV 2023 · 被引用 188 次
- Visual in-Context PromptingFeng Li, Qing Jiang, Hao Zhang, Tianhe Ren 等CVPR 2024
- Visual Prompting via Image InpaintingAmir Bar, Yossi Gandelsman, Trevor Darrell, Amir Globerson 等NeurIPS 2022 · 被引用 340 次
- In-Context Learning Unlocked for Diffusion ModelsZhendong Wang, Yifan Jiang, Yadong Lu, Yelong Shen 等NeurIPS 2023 · 被引用 128 次
