Computer Vision and Image Understanding

Papers
(The H4-Index of Computer Vision and Image Understanding is 28. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-10-01 to 2025-10-01.)
ArticleCitations
Editorial Board286
Editorial Board232
Editorial Board147
Editorial Board109
Luminance prior guided Low-Light 4C catenary image enhancement105
Editorial Board91
Improving the planarity and sharpness of monocularly estimated depth images using the Phong reflection model88
Exploring using jigsaw puzzles for out-of-distribution detection84
Siamese self-supervised learning for fine-grained visual classification76
Deducing health cues from biometric data71
3D semantic segmentation based on spatial-aware convolution and shape completion for augmented reality applications49
Convolutional neural network framework for deepfake detection: A diffusion-based approach45
Twin-SegNet: Dynamically coupled complementary segmentation networks for generalized medical image segmentation40
Feature reconstruction and metric based network for few-shot object detection39
RetSeg3D: Retention-based 3D semantic segmentation for autonomous driving38
Exploring the differences in adversarial robustness between ViT- and CNN-based models using novel metrics36
Efficient cross-information fusion decoder for semantic segmentation36
Emerging image generation with flexible control of perceived difficulty35
CRML-Net: Cross-Modal Reasoning and Multi-Task Learning Network for tooth image segmentation34
Extending function mixture network for improved spectral super-resolution33
Modality adaptation via feature difference learning for depth human parsing31
MATTE: Multi-task multi-scale attention30
Robust Teacher: Self-correcting pseudo-label-guided semi-supervised learning for object detection30
Lightweight feature point detection network with channel enhancement30
Editorial Board29
Editorial Board29
RelFormer: Advancing contextual relations for transformer-based dense captioning28
GaitBranch: A multi-branch refinement model combined with frame-channel attention mechanism for gait recognition28
PConvSRGAN: Real-world super-resolution reconstruction with pure convolutional networks28
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