SOTAVerified

Feature Compression

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 76–96 of 96 papers

TitleStatusHype
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
Selective Feature Compression for Efficient Activity Recognition Inference—0
Semantic and Effective Communication for Remote Control Tasks with Dynamic Feature Compression—0
SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks—0
Flexible Variable-Rate Image Feature Compression for Edge-Cloud SystemsCode0
Supervised Feature Compression based on Counterfactual AnalysisCode0
Entropy Loss: An Interpretability Amplifier of 3D Object Detection Network for Intelligent DrivingCode0
SC2 Benchmark: Supervised Compression for Split ComputingCode0
Selective Complementary Feature Fusion and Modal Feature Compression Interaction for Brain Tumor SegmentationCode0
Efficient Feature Compression for Edge-Cloud SystemsCode0
End-to-end Feature Selection Approach for Learning Skinny TreesCode0
TransVFC: A Transformable Video Feature Compression Framework for MachinesCode0
BottleNet++: An End-to-End Approach for Feature Compression in Device-Edge Co-Inference SystemsCode0
SGCN: Exploiting Compressed-Sparse Features in Deep Graph Convolutional Network AcceleratorsCode0
Understanding Deep Representation Learning via Layerwise Feature Compression and DiscriminationCode0
Effective Communication with Dynamic Feature CompressionCode0
Context-aware Deep Feature Compression for High-speed Visual TrackingCode0
Context-Aware Compilation of DNN Training Pipelines across Edge and CloudCode0
Show:102550
← PrevPage 4 of 4Next →

No leaderboard results yet.