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Feature Compression

Compress data for machine interpretability to perform downstream tasks, rather than for human perception.

Papers

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Showing 1–50 of 96 papers

TitleStatusHype
Meissonic: Revitalizing Masked Generative Transformers for Efficient High-Resolution Text-to-Image SynthesisCode3
Video in 10 Bits: Few-Bit VideoQA for Efficiency and PrivacyCode2
LLaVA-ST: A Multimodal Large Language Model for Fine-Grained Spatial-Temporal UnderstandingCode2
EMIFF: Enhanced Multi-scale Image Feature Fusion for Vehicle-Infrastructure Cooperative 3D Object DetectionCode2
WidthFormer: Toward Efficient Transformer-based BEV View TransformationCode2
I^2VC: A Unified Framework for Intra- & Inter-frame Video CompressionCode1
VIMI: Vehicle-Infrastructure Multi-view Intermediate Fusion for Camera-based 3D Object DetectionCode1
Compressing Features for Learning with Noisy LabelsCode1
Vector Quantization for Recommender Systems: A Review and OutlookCode1
Lossy Compression for Lossless PredictionCode1
Learning to Manipulate Artistic ImagesCode1
FOOL: Addressing the Downlink Bottleneck in Satellite Computing with Neural Feature CompressionCode1
FrankenSplit: Efficient Neural Feature Compression with Shallow Variational Bottleneck Injection for Mobile Edge ComputingCode1
Supervised Compression for Resource-Constrained Edge Computing SystemsCode1
Multi-Agent Collaborative Inference via DNN Decoupling: Intermediate Feature Compression and Edge LearningCode1
DeepAdaIn-Net: Deep Adaptive Device-Edge Collaborative Inference for Augmented Reality—0
Deep feature compression for collaborative object detection—0
Joint Device-Edge Inference over Wireless Links with Pruning—0
Deep Reinforcement Learning for Wireless Resource Allocation Using Buffer State Information—0
Derivation of Information-Theoretically Optimal Adversarial Attacks with Applications to Robust Machine Learning—0
Distilling Channels for Efficient Deep Tracking—0
Distributed and Rate-Adaptive Feature Compression—0
DMOFC: Discrimination Metric-Optimized Feature Compression—0
Dual-Domain Homogeneous Fusion with Cross-Modal Mamba and Progressive Decoder for 3D Object Detection—0
Dynamic Semantic Compression for CNN Inference in Multi-access Edge Computing: A Graph Reinforcement Learning-based Autoencoder—0
Dynamic Submodular Maximization—0
End-to-End Facial Deep Learning Feature Compression with Teacher-Student Enhancement—0
End-to-End Learnable Multi-Scale Feature Compression for VCM—0
Enhancing Drug Discovery: Autoencoder-Based Latent Space Augmentation for Improved Molecular Solubility Prediction using LatMixSol—0
Feature Compression for Cloud-Edge Multimodal 3D Object Detection—0
Feature Compression for Rate Constrained Object Detection on the Edge—0
Fusion: Towards Automated ICD Coding via Feature Compression—0
Generative Map Priors for Collaborative BEV Semantic Segmentation—0
Haar Wavelet Feature Compression for Quantized Graph Convolutional Networks—0
Hierarchical Semantic Compression for Consistent Image Semantic Restoration—0
In Defense of Clip-based Video Relation Detection—0
Intermediate Deep Feature Compression: the Next Battlefield of Intelligent Sensing—0
JointRF: End-to-End Joint Optimization for Dynamic Neural Radiance Field Representation and Compression—0
Large Scale Autonomous Driving Scenarios Clustering with Self-supervised Feature Extraction—0
Connecting Compression Spaces with Transformer for Approximate Nearest Neighbor Search—0
The Road to On-board Change Detection: A Lightweight Patch-Level Change Detection Network via Exploring the Potential of Pruning and Pooling—0
Adversarial Examples Detection with Enhanced Image Difference Features based on Local Histogram Equalization—0
An Efficient Large Recommendation Model: Towards a Resource-Optimal Scaling Law—0
An Emerging Coding Paradigm VCM: A Scalable Coding Approach Beyond Feature and Signal—0
Attention-based Feature Compression for CNN Inference Offloading in Edge Computing—0
Categorical Feature Compression via Submodular Optimization—0
Chromatic Learning for Sparse Datasets—0
Collaborative Intelligence: Challenges and Opportunities—0
Communication-Computation Efficient Device-Edge Co-Inference via AutoML—0
Compact Representation for Image Classification: To Choose or to Compress?—0
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