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Works291 from public data
- Hexagon-based search pattern for fast block motion estimation897
Analysis shows that a speed improvement rate of the hexagon-based search (HEXBS) algorithm over the diamond search (DS) algorithm can be over 80% for locating some motion vectors in certain scenarios.
- Low-Light Image Enhancement with Normalizing Flow650
This paper investigates to model this one-to-many relationship via a proposed normalizing flow model of an invertible network that takes the low-light images/features as the condition and learns to map the distribution of normally exposed images into a Gaussian distribution.
- SinSR: Diffusion-Based Image Super-Resolution in a Single Step378
This work first derive a deterministic sampling process from the most recent state-of-the-art (SOTA) method for accelerating diffusion-based SR, which can be distilled into a student model that performs SR within only one inference step, resulting in a remarkable up to × 10 speedup for inference.
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- Robust Video Content Alignment and Compensation for Rain Removal in a CNN Framework204
A novel derain algorithm is proposed, which applies superpixel (SP) segmentation to decompose the scene into depth consistent units and shows that much cleaner rain removal is achieved especially for highly dynamic scenes with heavy and opaque rainfall from a fast moving camera.
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- Light Field Compression With Disparity-Guided Sparse Coding Based on Structural Key Views106
An LF codec with disparity guided Sparse Coding over a learned perspective-shifted LF dictionary based on selected Structural Key Views (SC-SKV), which produces convincing compression results in terms of both rate-distortion performance and visual quality compared with Joint Exploration Model.
- Fast approach for H.264 inter mode decision101
Experimental results show that the proposed method can efficiently save the computation cost for inter mode decision while maintaining the same PSNR and bit rate.
- Rethinking and Designing a High-Performing Automatic License Plate Recognition Approach99
The proposed VSNet outperforms state-of-the-art methods by more than 50% relative improvement on error rate, achieving >99% recognition accuracy on CCPD and AOLP datasets with 149 FPS inference speed and illustrates an outstanding generalization capability when evaluated on the unseen PKUData and CLPD datasets.
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- ExposureDiffusion: Learning to Expose for Low-light Image Enhancement90
This work seamlessly integrating a diffusion model with a physics-based exposure model to achieve significantly improved performance and reduced inference time and proposes an adaptive residual layer that effectively screens out the side-effect in the iterative refinement when the intermediate results have been already well-exposed.
- A soft MAP framework for blind super-resolution image reconstruction87
A new soft maximum a posteriori (MAP) estimation framework to perform joint blur identification and HR image reconstruction that incorporates a soft blur prior that estimates the relevance of the best-fit parametric blur model, and induces reinforcement learning towards it.
- A survey on occupancy perception for autonomous driving: The information fusion perspective84
This survey reviews the most recent works on 3D occupancy perception, and provides in-depth analyses of methodologies with various input modalities, and evaluates and analyze the occupancy perception performance of the state-of-the-art on the most popular datasets.
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- TAFNet: A Three-Stream Adaptive Fusion Network for RGB-T Crowd Counting73
A three-stream adaptive fusion network named TAFNet, which uses paired RGB and thermal images for crowd counting, which achieves more than 20% improvement on mean average error and root mean squared error compared with state-of-the-art method.
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- A motion vector recovery algorithm for digital video using lagrange interpolation64
This paper proposes an efficient motion vector recovery algorithm for the new coding standard H.264, which makes use of the Lagrange interpolation formula, and shows that the algorithm can efficiently improve the visual quality of corrupted video.
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 2026-10-12. 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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