L-CoIns: Language-based Colorization With Instance Awareness
Zheng Chang, Shuchen Weng, Peixuan Zhang, Yu Li, Si Li, Boxin Shi
Abstract
The right woman is dressed in shirt of violet color. L-CoDe L-CoDer Ours ML2018 The middle woman is dressed in orange and the right woman in yellow. L-CoDe L-CoDer Ours ML2018 Three women are dressed in pink. L-CoDe L-CoDer Ours ML2018 The middle woman is dressed in yellow, the left woman in blue, the right woman in red. L-CoDe L-CoDer Ours ML2018 Grayscale Figure 1. Language-based colorization results given four different language descriptions, compared with ML2018 [29], L-CoDe [42], and L-CoDer [6]. Top left: For the description that has clear correspondences between color words and object words, our method correctly colorizes all corresponding regions. Top right: For the description that assigns distinct colors for every instance corresponding to the same object words, our model predicts the exact correspondence between the instance region and the color word. Botton left: For the description that includes unobserved correspondences between color words and object words, our method could adaptively parse the sentence and determine the correct semantics for colorization. Bottom right: For the description that is against the statistical correlation between luminance and color words, our method shows the robustness and colorize description-consistent results.
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Cited by top-tier papers12
- L-CAD: Language-based Colorization with Any-level Descriptions using Diffusion PriorsZheng Chang, Shuchen Weng, Peixuan Zhang, Yu Li et al.NeurIPS 2023 · 42 citations
- Affective Image Filter: Reflecting Emotions from Text to ImagesShuchen Weng, Peixuan Zhang, Zheng Chang, Xinlong Wang et al.ICCV 2023 · 25 citations
- Language-guided Image Reflection SeparationHaofeng Zhong, Yuchen Hong, Shuchen Weng, Jinxiu Liang et al.CVPR 2024 · 14 citations
- LuminAIRe: Illumination-Aware Conditional Image Repainting for Lighting-Realistic GenerationJiajun Tang, Haofeng Zhong, Shuchen Weng, Boxin ShiNeurIPS 2023 · 6 citations
- Pre-training LiDAR-based 3D Object Detectors through ColorizationTai-Yu Pan, Chenyang Ma, Tianle Chen, Cheng Perng Phoo et al.ICLR 2024 · 5 citations
Builds on18
- An Image is Worth 16x16 Words: Transformers for Image Recognition at ScaleAlexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn et al.ICLR 2021 · 21,477 citations
- Deformable DETR: Deformable Transformers for End-to-End Object DetectionXizhou Zhu, Weijie Su, Lewei Lu, Bin Li et al.ICLR 2021 · 7,353 citations
- Zero-Shot Text-to-Image GenerationAditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray et al.ICML 2021 · 6,356 citations
- ViLT: Vision-and-Language Transformer Without Convolution or Region SupervisionWonjae Kim, Bokyung Son, Ildoo KimICML 2021 · 2,258 citations
- MDETR - Modulated Detection for End-to-End Multi-Modal UnderstandingAishwarya Kamath, Mannat Singh, Yann LeCun, Gabriel Synnaeve et al.ICCV 2021 · 1,114 citations
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