activity
20232025
most citedToward Real World Stereo Image Super-Resolution via Hybrid Degradation Model and Discriminator for Implied Stereo Image Information

1 citations · 1 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2025

From Noisy Labels to Intrinsic Structure: A Geometric-Structural Dual-Guided Framework for Noise-Robust Medical Image Segmentation

Tao Wang, Zhenxuan Zhang, Yuanbo Zhou +5

The effectiveness of convolutional neural networks in medical image segmentation relies on large-scale, high-quality annotations, which are costly and time-consuming to obtain. Eve…

cs.CV2024

Synergy-Guided Regional Supervision of Pseudo Labels for Semi-Supervised Medical Image Segmentation

Tao Wang, Xinlin Zhang, Yuanbin Chen +4

Semi-supervised learning has received considerable attention for its potential to leverage abundant unlabeled data to enhance model robustness. Pseudo labeling is a widely used str…

cs.CV2024

ScribbleVS: Scribble-Supervised Medical Image Segmentation via Dynamic Competitive Pseudo Label Selection

Tao Wang, Xinlin Zhang, Zhenxuan Zhang +7

In clinical medicine, precise image segmentation can provide substantial support to clinicians. However, obtaining high-quality segmentation typically demands extensive pixel-level…

cs.CV2024

DIffSteISR: Harnessing Diffusion Prior for Superior Real-world Stereo Image Super-Resolution

Yuanbo Zhou, Xinlin Zhang, Wei Deng +4

We introduce DiffSteISR, a pioneering framework for reconstructing real-world stereo images. DiffSteISR utilizes the powerful prior knowledge embedded in pre-trained text-to-image…

cs.CV2024

ASteISR: Adapting Single Image Super-resolution Pre-trained Model for Efficient Stereo Image Super-resolution

Yuanbo Zhou, Yuyang Xue, Wei Deng +3

Despite advances in the paradigm of pre-training then fine-tuning in low-level vision tasks, significant challenges persist particularly regarding the increased size of pre-trained…

eess.IV2024

Innovative Quantitative Analysis for Disease Progression Assessment in Familial Cerebral Cavernous Malformations

Ruige Zong, Tao Wang, Chunwang Li +8

Familial cerebral cavernous malformation (FCCM) is a hereditary disorder characterized by abnormal vascular structures within the central nervous system. The FCCM lesions are often…

eess.IV2023★ 1 cited

Toward Real World Stereo Image Super-Resolution via Hybrid Degradation Model and Discriminator for Implied Stereo Image Information

Yuanbo Zhou, Yuyang Xue, Jiang Bi +8

Real-world stereo image super-resolution has a significant influence on enhancing the performance of computer vision systems. Although existing methods for single-image super-resol…

eess.IV2023

Pseudo Label-Guided Data Fusion and Output Consistency for Semi-Supervised Medical Image Segmentation

Tao Wang, Yuanbin Chen, Xinlin Zhang +7

Supervised learning algorithms based on Convolutional Neural Networks have become the benchmark for medical image segmentation tasks, but their effectiveness heavily relies on a la…