Computer Vision and Image Understanding

Papers
(The H4-Index of Computer Vision and Image Understanding is 30. 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 2022-01-01 to 2026-01-01.)
ArticleCitations
Luminance prior guided Low-Light 4C catenary image enhancement320
Editorial Board252
Efficient cross-information fusion decoder for semantic segmentation123
3D semantic segmentation based on spatial-aware convolution and shape completion for augmented reality applications113
Editorial Board100
Robust Teacher: Self-correcting pseudo-label-guided semi-supervised learning for object detection100
Improving the planarity and sharpness of monocularly estimated depth images using the Phong reflection model93
Editorial Board85
Exploring using jigsaw puzzles for out-of-distribution detection74
Extending function mixture network for improved spectral super-resolution54
MATTE: Multi-task multi-scale attention52
Editorial Board47
Editorial Board45
Modality adaptation via feature difference learning for depth human parsing40
Exploring the differences in adversarial robustness between ViT- and CNN-based models using novel metrics38
Feature reconstruction and metric based network for few-shot object detection38
Emerging image generation with flexible control of perceived difficulty37
Lightweight feature point detection network with channel enhancement37
REST: A resolution preserving network for photorealistic style transfer via semantic distillation35
CRML-Net: Cross-Modal Reasoning and Multi-Task Learning Network for tooth image segmentation35
Convolutional neural network framework for deepfake detection: A diffusion-based approach35
Deducing health cues from biometric data35
Twin-SegNet: Dynamically coupled complementary segmentation networks for generalized medical image segmentation34
RetSeg3D: Retention-based 3D semantic segmentation for autonomous driving34
Siamese self-supervised learning for fine-grained visual classification33
PConvSRGAN: Real-world super-resolution reconstruction with pure convolutional networks32
RelFormer: Advancing contextual relations for transformer-based dense captioning32
GaitBranch: A multi-branch refinement model combined with frame-channel attention mechanism for gait recognition31
Editorial Board31
Editorial Board30
Improved Short-term Dense Bottleneck network for efficient scene analysis30
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