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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 41–50 of 96 papers

TitleStatusHype
Memory-Efficient CNN Accelerator Based on Interlayer Feature Map Compression—0
Mitigating severe over-parameterization in deep convolutional neural networks through forced feature abstraction and compression with an entropy-based heuristic—0
MotionBench: Benchmarking and Improving Fine-grained Video Motion Understanding for Vision Language Models—0
Near-Lossless Deep Feature Compression for Collaborative Intelligence—0
NeRFCodec: Neural Feature Compression Meets Neural Radiance Fields for Memory-Efficient Scene Representation—0
Reconstructing Pruned Filters using Cheap Spatial Transformations—0
PIDNet: An Efficient Network for Dynamic Pedestrian Intrusion Detection—0
Pixel-Level Matching for Video Object Segmentation using Convolutional Neural Networks—0
Privacy-Aware Multi-Device Cooperative Edge Inference with Distributed Resource Bidding—0
Revisit Visual Representation in Analytics Taxonomy: A Compression Perspective—0
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