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eess.IV2026

Dual-Prior Guided Null-Space Learning with Mixture-of-Splines for Arbitrary Medical Slice Super-Resolution

Haofei Song, Siyuan Xu, Xintian Mao +3

Arbitrary slice super-resolution reconstructs isotropic volumes from anisotropic clinical acquisitions by synthesizing intermediate slices at arbitrary scales. However, treating th…

eess.IV2025

Fast Training-free Perceptual Image Compression

Ziran Zhu, Tongda Xu, Minye Huang +5

Training-free perceptual image codec adopt pre-trained unconditional generative model during decoding to avoid training new conditional generative model. However, they heavily rely…

eess.IV2025

CAMSIC: Content-aware Masked Image Modeling Transformer for Stereo Image Compression

Xinjie Zhang, Shenyuan Gao, Zhening Liu +6

Existing learning-based stereo image codec adopt sophisticated transformation with simple entropy models derived from single image codecs to encode latent representations. However,…

eess.IV2024

GaussianImage: 1000 FPS Image Representation and Compression by 2D Gaussian Splatting

Xinjie Zhang, Xingtong Ge, Tongda Xu +6

Implicit neural representations (INRs) recently achieved great success in image representation and compression, offering high visual quality and fast rendering speeds with 10-1000…

eess.IV2024

Super-High-Fidelity Image Compression via Hierarchical-ROI and Adaptive Quantization

Jixiang Luo, Yan Wang, Hongwei Qin

Learned Image Compression (LIC) has achieved dramatic progress regarding objective and subjective metrics. MSE-based models aim to improve objective metrics while generative models…

eess.IV2024

Task-Aware Encoder Control for Deep Video Compression

Xingtong Ge, Jixiang Luo, Xinjie Zhang +7

Prior research on deep video compression (DVC) for machine tasks typically necessitates training a unique codec for each specific task, mandating a dedicated decoder per task. In c…