Modality adaptation via feature difference learning for depth human parsing
-
Published:2024-10
Issue:
Volume:247
Page:104070
-
ISSN:1077-3142
-
Container-title:Computer Vision and Image Understanding
-
language:en
-
Short-container-title:Computer Vision and Image Understanding
Author:
Huang Shaofei, Hui TianruiORCID, Gong Yue, Peng Fengguang, Fang Yuqiang, Wang Jingwei, Ma Bin, Wei Xiaoming, Han Jizhong
Reference68 articles.
1. Self-supervised multimodal versatile networks;Alayrac;Adv. Neural Inf. Process. Syst.,2020 2. Andriluka, M., Pishchulin, L., Gehler, P., Schiele, B., 2014. 2d human pose estimation: New benchmark and state of the art analysis. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 3686–3693. 3. Segnet: A deep convolutional encoder-decoder architecture for image segmentation;Badrinarayanan;IEEE Trans. Pattern Anal. Mach. Intell.,2017 4. Cao, J., Leng, H., Lischinski, D., Cohen-Or, D., Tu, C., Li, Y., 2021. Shapeconv: Shape-aware convolutional layer for indoor rgb-d semantic segmentation. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 7088–7097. 5. Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs;Chen;IEEE Trans. Pattern Anal. Mach. Intell.,2017
|
|