SOTAVerified

Computational Efficiency

Methods and optimizations to reduce the computational resources (e.g., time, memory, or power) needed for training and inference in models. This involves techniques that streamline processing, optimize algorithms, or leverage hardware to enhance performance without compromising accuracy.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 691–700 of 4891 papers

TitleStatusHype
Facial Emotion Recognition: State of the Art Performance on FER2013Code1
Adaptive Focus for Efficient Video RecognitionCode1
UVStyle-Net: Unsupervised Few-shot Learning of 3D Style Similarity Measure for B-RepsCode1
The 5th AI City ChallengeCode1
Consistent Accelerated Inference via Confident Adaptive TransformersCode1
Pyramidal Reservoir Graph Neural NetworkCode1
CondenseNet V2: Sparse Feature Reactivation for Deep NetworksCode1
Cloth-Changing Person Re-identification from A Single Image with Gait Prediction and RegularizationCode1
Checkerboard Context Model for Efficient Learned Image CompressionCode1
Deep Implicit Moving Least-Squares Functions for 3D ReconstructionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified