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- Multi-Agent Image Restoration26
A real-world degradation prior is introduced, categorizing degradations into three types: (1) scene, (2) imaging, and (3) compression, which are observed to occur sequentially in real world, and reverse them in the opposite order.
- Reversible Data Hiding Scheme Based on Adjusting Pixel Modulation and Block-Wise Compression for Encrypted Images24
In IPBTL-RDHEI, an adjusting pixel modulation strategy is considered to reduce the probability of the overflow of pixels, making more embeddable pixels usage to carry secret data.
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- Parameter Efficient Adaptation for Image Restoration with Heterogeneous Mixture-of-Experts15
The proposed AdaptIR is a Mixture-of-Experts (MoE) with orthogonal multi-branch design to capture local spatial, global spatial, and channel representation bases, followed by adaptive base combination to obtain heterogeneous representation for different degradations.
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- Mixing high-dimensional features for JPEG steganalysis with ensemble classifier8
This paper combines three current feature sets and removes the unimportant features according to the correlation between different features parts so as to form a new feature space used for steganalysis and designs a proportion mechanism to manage the feature selection in two subspaces for each base learners of the ensemble classifier.
- Layerwise Adversarial Learning for Image Steganography6
A layerwise adversarial training method that added a single-layer subnetwork and a discriminator behind each layer to capture their representational power.
- A realization of semi-global matching stereo algorithm on GPU for real-time application6
A real-time SGM realization on Graphics Processing Unit (GPU) is introduced and CUDA, a general purpose parallel computing architecture introduced by NVIDIA in November 2006, has been used to realize the algorithm.
- Coherent Path Tracing6
This paper proposes an interleaved sampling scheme that reduces the correlation in the noise and makes it virtually imperceptible in the final image, while producing images with similar RMS error values.
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- Steganalysis in High-Dimensional Feature Space Using Selective Ensemble Classifiers2
A frame of selective ensemble classifiers is proposed as an alternative to SVM for steganalysis by applying the selective theory that ensemble some instead of all the available base learners.
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- Visual odometry based on camera motion and bidirectional long short-term memory network–
A monocular visual odometry method that combines the camera's own motion estimation and a bidirectional long-short-term memory network is proposed that can estimate the pose with higher accuracy and more accurate six-degree-of-freedom camera pose information can be obtained.
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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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