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Image fusion integrates essential information from multiple images into a single composite, enhancing structures, textures, and refining imperfections.
Medical image fusion: A survey of the state of the art
James, A. P. and Dasarathy, B. V · 2014
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Multi-focus image fusion using dictionary-based sparse representation
Nejati, M., Samavi, S., and Shirani, S · 2015
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Show, attend and tell: Neural image caption generation with visual attention
Xu, K., Ba, J., Kiros, R., Cho, K., Courville, A., Salakhudinov, R., Zemel, R., and Bengio, Y · 2015
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Deep residual learning for image recognition
He, K., Zhang, X., Ren, S., and Sun, J · 2016
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Multi-focus image fusion with a deep convolutional neural network
Liu, Y., Chen, X., Peng, H., and Wang, Z · 2017
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Robust multi-exposure image fusion: A structural patch decomposition approach
Ma, K., Li, H., Yong, H., Wang, Z., Meng, D., and Zhang, L · 2017
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Deepfuse: A deep unsupervised approach for exposure fusion with extreme exposure image pairs
Prabhakar, K. R., Srikar, V. S., and Babu, R. V · 2017
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Learning a deep single image contrast enhancer from multi-exposure images
Cai, J., Gu, S., and Zhang, L · 2018
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Densefuse: A fusion approach to infrared and visible images
Li, H. and Wu, X.-J · 2018
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Fusegan: Learning to fuse multi-focus image via conditional generative adversarial network
Guo, X., Nie, R., Cao, J., Zhou, D., Mei, L., and He, K · 2019
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Unsupervised deep image fusion with structure tensor representations
Jung, H., Kim, Y., Jang, H., Ha, N., and Sohn, K · 2020
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Global-feature encoding u-net (geu-net) for multi-focus image fusion
Xiao, B., Xu, B., Bi, X., and Li, W · 2020
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DIDFuse: Deep image decomposition for infrared and visible image fusion
Zhao, Z., Xu, S., Zhang, C., Liu, J., Zhang, J., and Li, P · 2020
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Deep convolutional neural network for multi-modal image restoration and fusion
Deng, X. and Dragotti, P. L · 2021
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Deep coupled feedback network for joint exposure fusion and image super-resolution
Deng, X., Zhang, Y., Xu, M., Gu, S., and Duan, Y · 2021
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Learning transferable visual models from natural language supervision
Radford, A., Kim, J. W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al · 2021
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Zero-shot text-to-image generation
Ramesh, A., Pavlov, M., Goh, G., Gray, S., Voss, C., Radford, A., Chen, M., and Sutskever, I · 2021
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Simvlm: Simple visual language model pretraining with weak supervision
Wang, Z., Yu, J., Yu, A. W., Dai, Z., Tsvetkov, Y., and Cao, Y · 2021
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Dtmnet: a discrete tchebichef moments-based deep neural network for multi-focus image fusion
Xiao, B., Wu, H., and Bi, X · 2021
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Emfusion: An unsupervised enhanced medical image fusion network
Xu, H. and Ma, J · 2021
Cited alongside, same era.
Deep gradient projection networks for pan-sharpening
Xu, S., Zhang, J., Zhao, Z., Sun, K., Liu, J., and Zhang, C · 2021
Cited alongside, same era.
Sdnet: A versatile squeeze-and-decomposition network for real-time image fusion
Zhang, H. and Ma, J · 2021
Cited alongside, same era.
Multi-modal convolutional dictionary learning
Instructpix2pix: Learning to follow image editing instructions
Brooks, T., Holynski, A., and Efros, A. A · 2023
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Mutual-guided dynamic network for image fusion
Guan, Y., Xu, R., Yao, M., Wang, L., and Xiong, Z · 2023
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Zmff: Zero-shot multi-focus image fusion
Hu, X., Jiang, J., Liu, X., and Ma, J · 2023
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Segment anything
Kirillov, A., Mintun, E., Ravi, N., Mao, H., Rolland, C., Gustafson, L., Xiao, T., Whitehead, S., Berg, A. C., Lo, W.-Y., Dollar, P., and Girshick, R · 2023
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OpenAI · 2023
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ChatGPT , 2023
OpenAI · 2023
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Gao, F., Deng, X., Xu, M., Xu, J., and Dragotti, P. L · 2022
Cited alongside, same era.
Multi-exposure image fusion via deep perceptual enhancement
Han, D., Li, L., Guo, X., and Ma, J · 2022
Cited alongside, same era.
Towards all weather and unobstructed multi-spectral image stitching: Algorithm and benchmark
Jiang, Z., Zhang, Z., Fan, X., and Liu, R · 2022
Cited alongside, same era.
BLIP: bootstrapping language-image pre-training for unified vision-language understanding and generation
Li, J., Li, D., Xiong, C., and Hoi, S. C. H · 2022
Cited alongside, same era.
Fusion from decomposition: A self-supervised decomposition approach for image fusion
Liang, P., Jiang, J., Liu, X., and Ma, J · 2022
Cited alongside, same era.
Grit: Faster and better image captioning transformer using dual visual features
Nguyen, V.-Q., Suganuma, M., and Okatani, T · 2022
Cited alongside, same era.
Transmef: A transformer-based multi-exposure image fusion framework using self-supervised multi-task learning
Qu, L., Liu, S., Wang, M., and Song, Z · 2022
Cited alongside, same era.
Touvron, H., Lavril, T., Izacard, G., Martinet, X., Lachaux, M.-A., Lacroix, T., Rozière, B., Goyal, N., Hambro, E., Azhar, F., et al · 2023
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When multi-focus image fusion networks meet traditional edge-preservation technology
Wang, Z., Li, X., Zhao, L., Duan, H., Wang, S., Liu, H., and Zhang, X · 2023
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Msgfusion: Medical semantic guided two-branch network for multimodal brain image fusion
Wen, J., Qin, F., Du, J., Fang, M., Wei, X., Chen, C. P., and Li, P · 2023
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MURF: mutually reinforcing multi-modal image registration and fusion
Xu, H., Yuan, J., and Ma, J · 2023
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Gpt4roi: Instruction tuning large language model on region-of-interest
Zhang, S., Sun, P., Chen, S., Xiao, M., Shao, W., Zhang, W., Chen, K., and Luo, P · 2023
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Visible and infrared image fusion using deep learning
Zhang, X. and Demiris, Y · 2023
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Image.txt: Transform image into unique paragraph
Zhao, H · 2023
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Minigpt-4: Enhancing vision-language understanding with advanced large language models
Zhu, D., Chen, J., Shen, X., Li, X., and Elhoseiny, M · 2023
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Billm: Pushing the limit of post-training quantization for llms
Huang, W., Liu, Y., Qin, H., Li, Y., Zhang, S., Liu, X., Magno, M., and Qi, X · 2024
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Accurate lora-finetuning quantization of llms via information retention
Qin, H., Ma, X., Zheng, X., Li, X., Zhang, Y., Liu, S., Luo, J., Liu, X., and Magno, M · 2024
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