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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 31–40 of 96 papers

TitleStatusHype
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
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