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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
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
Video in 10 Bits: Few-Bit VideoQA for Efficiency and PrivacyCode2
I^2VC: A Unified Framework for Intra- & Inter-frame Video CompressionCode1
Vector Quantization for Recommender Systems: A Review and OutlookCode1
FOOL: Addressing the Downlink Bottleneck in Satellite Computing with Neural Feature CompressionCode1
Learning to Manipulate Artistic ImagesCode1
VIMI: Vehicle-Infrastructure Multi-view Intermediate Fusion for Camera-based 3D Object DetectionCode1
FrankenSplit: Efficient Neural Feature Compression with Shallow Variational Bottleneck Injection for Mobile Edge ComputingCode1
Compressing Features for Learning with Noisy LabelsCode1
Multi-Agent Collaborative Inference via DNN Decoupling: Intermediate Feature Compression and Edge LearningCode1
Supervised Compression for Resource-Constrained Edge Computing SystemsCode1
Lossy Compression for Lossless PredictionCode1
Cross-architecture universal feature coding via distribution alignment—0
Enhancing Drug Discovery: Autoencoder-Based Latent Space Augmentation for Improved Molecular Solubility Prediction using LatMixSol—0
SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks—0
UCS: A Universal Model for Curvilinear Structure Segmentation—0
TransVFC: A Transformable Video Feature Compression Framework for MachinesCode0
Selective Complementary Feature Fusion and Modal Feature Compression Interaction for Brain Tumor SegmentationCode0
Task-Oriented Feature Compression for Multimodal Understanding via Device-Edge Co-Inference—0
Dual-Domain Homogeneous Fusion with Cross-Modal Mamba and Progressive Decoder for 3D Object Detection—0
Hierarchical Semantic Compression for Consistent Image Semantic Restoration—0
Stereo Image Coding for Machines with Joint Visual Feature Compression—0
An Efficient Large Recommendation Model: Towards a Resource-Optimal Scaling Law—0
MotionBench: Benchmarking and Improving Fine-grained Video Motion Understanding for Vision Language Models—0
Generative Map Priors for Collaborative BEV Semantic Segmentation—0
Privacy-Aware Multi-Device Cooperative Edge Inference with Distributed Resource Bidding—0
Structurally Consistent MRI Colorization using Cross-modal Fusion Learning—0
SpikeBottleNet: Spike-Driven Feature Compression Architecture for Edge-Cloud Co-Inference—0
Toward Scalable Image Feature Compression: A Content-Adaptive and Diffusion-Based Approach—0
Distilling Channels for Efficient Deep Tracking—0
Feature Compression for Cloud-Edge Multimodal 3D Object Detection—0
Entropy Loss: An Interpretability Amplifier of 3D Object Detection Network for Intelligent DrivingCode0
Towards unlocking the mystery of adversarial fragility of neural networks—0
Texture-guided Coding for Deep Features—0
JointRF: End-to-End Joint Optimization for Dynamic Neural Radiance Field Representation and Compression—0
Compressive Feature Selection for Remote Visual Multi-Task Inference—0
DMOFC: Discrimination Metric-Optimized Feature Compression—0
Distributed and Rate-Adaptive Feature Compression—0
NeRFCodec: Neural Feature Compression Meets Neural Radiance Fields for Memory-Efficient Scene Representation—0
Flexible Variable-Rate Image Feature Compression for Edge-Cloud SystemsCode0
The Geometric Structure of Topic Models—0
Effective Communication with Dynamic Feature CompressionCode0
Dynamic Semantic Compression for CNN Inference in Multi-access Edge Computing: A Graph Reinforcement Learning-based Autoencoder—0
Vertical Federated Image Segmentation—0
Understanding Deep Representation Learning via Layerwise Feature Compression and DiscriminationCode0
End-to-end Feature Selection Approach for Learning Skinny TreesCode0
The Road to On-board Change Detection: A Lightweight Patch-Level Change Detection Network via Exploring the Potential of Pruning and Pooling—0
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