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- Baolong GuoSuggested from co-authorship
- Jeng‐Shyang PanSuggested from co-authorship
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Works299 from public data
- MetaIQA: Deep Meta-Learning for No-Reference Image Quality Assessment442
A no-reference IQA metric based on deep meta-learning that outperforms the state-of-the-arts by a large margin and can be easily generalized to authentic distortions, which is highly desired in real-world applications of IQA metrics.
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- No-Reference and Robust Image Sharpness Evaluation Based on Multiscale Spatial and Spectral Features144
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- Personalized Image Aesthetics Assessment with Rich Attributes132
Experimental results indicate that the conditional PIAA model can outperform the control group, which is also the first attempt to demonstrate how image aesthetics and subject characters interact to produce the intricate personalized tastes on image aesthetics.
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- Geometrically invariant image watermarking using Polar Harmonic Transforms119
Experimental results illustrate that the proposed scheme outperforms ZM/PZM based schemes in terms of embedding capacity and watermark robustness and is also robust to both geometric and signal processing based attacks.
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- Orientation selectivity based visual pattern for reduced-reference image quality assessment98
Experimental results on five public databases demonstrate that the proposed RR IQA method has performance consistent with the human perception under a small amount of reference data (only 9 values).
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- AesBench: An Expert Benchmark for Multimodal Large Language Models on Image Aesthetics Perception96
An Expert-labeled Aesthetics Perception Database (EAPD), which features diversified image contents and high-quality annotations provided by professional aesthetic experts, and a set of integrative criteria to measure the aesthetic perception abilities of MLLMs from four perspectives.
- RIRNet96
This work proposes a novel no-reference VQA framework named Recurrent-In-Recurrent Network (RIRNet), which integrates concepts from motion perception in human visual system (HVS), which is manifested in the designed network structure composed of low- and high- level processing.
- Detecting copy-move forgery under affine transforms for image forensics94
A method for detecting this kind of image tampering based on circular pattern matching using Polar Harmonic Transform and lexicographically sorting the forged regions are detected by finding the similar block pairs after proper post-processing.
- AesExpert: Towards Multi-modality Foundation Model for Image Aesthetics Perception89
A comprehensively annotated Aesthetic Multi-Modality Instruction Tuning (AesMMIT) dataset is introduced, which serves as the footstone for building multi-modality aesthetics foundation models, achieving multi-modality Aesthetic Expert models, dubbed AesExpert.
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- An efficient forgery detection algorithm for object removal by exemplar-based image inpainting89
An efficient forgery detection algorithm for object removal by exemplar-based inpainting is presented, which integrates central pixel mapping (CPM), greatest zero-connectivity component labeling (GZCL) and fragment splicing detection (FSD).
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-14. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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