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Found 12 papers, 3 papers with code
Leveraging Diffusion Knowledge for Generative Image Compression with Fractal Frequency-Aware Band Learning
By optimizing the rate-distortion-realism trade-off, generative image compression approaches produce detailed, realistic images instead of the only sharp-looking reconstructions produced by rate-distortion-optimized models.
CLIMB: Data Foundations for Large Scale Multimodal Clinical Foundation Models
To bridge this gap, we introduce Clinical Large-Scale Integrative Multimodal Benchmark (CLIMB), a comprehensive clinical benchmark unifying diverse clinical data across imaging, language, temporal, and graph modalities.
An Information-Theoretic Regularizer for Lossy Neural Image Compression
Lossy image compression networks aim to minimize the latent entropy of images while adhering to specific distortion constraints.
Compact Visual Data Representation for Green Multimedia -- A Human Visual System Perspective
The Human Visual System (HVS), with its intricate sophistication, is capable of achieving ultra-compact information compression for visual signals.
RCNet: Deep Recurrent Collaborative Network for Multi-View Low-Light Image Enhancement
Recent single image-based enhancement methods may not be able to provide consistently desirable restoration performance for all views due to the ignorance of potential feature correspondence among different views.
Generative Visual Compression: A Review
Artificial Intelligence Generated Content (AIGC) is leading a new technical revolution for the acquisition of digital content and impelling the progress of visual compression towards competitive performance gains and diverse functionalities over traditional codecs.
2AFC Prompting of Large Multimodal Models for Image Quality Assessment
While abundant research has been conducted on improving high-level visual understanding and reasoning capabilities of large multimodal models~(LMMs), their visual quality assessment~(IQA) ability has been relatively under-explored.
Deep Shape-Texture Statistics for Completely Blind Image Quality Evaluation
The perceptual quality is quantified by the variant Mahalanobis Distance between the inner and outer Shape-Texture Statistics (DSTS), wherein the inner and outer statistics respectively describe the quality fingerprints of the distorted image and natural images.
Geometric Prior Based Deep Human Point Cloud Geometry Compression
The emergence of digital avatars has raised an exponential increase in the demand for human point clouds with realistic and intricate details.
Cold-Start based Multi-Scenario Ranking Model for Click-Through Rate Prediction
Online travel platforms (OTPs), e. g., Ctrip. com or Fliggy. com, can effectively provide travel-related products or services to users.
Refining HTN Methods via Task Insertion with Preferences
Hierarchical Task Network (HTN) planning is showing its power in real-world planning.
Combining Reinforcement Learning and Configuration Checking for Maximum k-plex Problem
Based on the BLP and DTCC, we develop a local search algorithm named BDCC and improve it by a hyperheuristic strategy.
