Fan, Deng-Ping

Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions

Wang, W., Xie, E., Li, X., Fan, D.-P., Song, K., Liang, D., Lu, T., Luo, P., & Shao, L. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 5,259

Pvt v2: Improved baselines with pyramid vision transformer

Wang, W., Xie, E., Li, X., Fan, D.-P., Song, K., Liang, D., Lu, T., Luo, P., & Shao, L. (2022) · Computational Visual Media

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 2,439

Structure-Measure: A New Way to Evaluate Foreground Maps

Fan, D.-P., Cheng, M.-M., Liu, Y., Li, T., & Borji, A. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV)

Visual Attention and Saliency DetectionAdvanced Neural Network Applications

Cited by 2,092

Segment anything model for medical images?

Huang, Y., Yang, X., Liu, L., Zhou, H., Chang, A., Zhou, X., Chen, R., Yu, J., Chen, J., Chen, C., et al. (2024) · Medical Image Analysis

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 536

UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders

Zhang, J., Fan, D.-P., Dai, Y., Anwar, S., Saleh, F. S., Zhang, T., & Barnes, N. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Visual Attention and Saliency DetectionAdvanced Neural Network Applications

Cited by 423

Salient Object Detection via Integrity Learning

Zhuge, M., Fan, D.-P., Liu, N., Zhang, D., Xu, D., & Shao, L. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Visual Attention and Saliency DetectionAdvanced Neural Network Applications

Cited by 403

RGB-D salient object detection: A survey

Zhou, T., Fan, D.-P., Cheng, M.-M., Shen, J., & Shao, L. (2021) · Computational Visual Media

Visual Attention and Saliency DetectionAdvanced Neural Network Applications

Cited by 331

SAM struggles in concealed scenes — empirical study on “Segment Anything”

Ji, G.-P., Fan, D.-P., Xu, P., Zhou, B., Cheng, M.-M., & Van Gool, L. (2023) · Science China Information Sciences

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 101

Mindstorms in Natural Language-Based Societies of Mind

Zhuge, M., Liu, H., Faccio, F., Ashley, D. R., Csordás, R., Gopalakrishnan, A., Hamdi, A., Hammoud, H. A. A. K., Herrmann, V., Irie, K., et al. (2023) · arXiv

Multimodal Machine Learning ApplicationsMulti-Agent Systems and Negotiation

Cited by 24

Mindstorms in Natural Language-Based Societies of Mind

Zhuge, M., Liu, H., Faccio, F., Ashley, D. R., Csordás, R., Gopalakrishnan, A., Hamdi, A., Hammoud, H. A. A. K., Herrmann, V., Irie, K., et al. (2025) · Computational Visual Media

Multimodal Machine Learning ApplicationsMulti-Agent Systems and Negotiation

Cited by 24