SOTAVerified

Quantization

Quantization is a promising technique to reduce the computation cost of neural network training, which can replace high-cost floating-point numbers (e.g., float32) with low-cost fixed-point numbers (e.g., int8/int16).

Source: Adaptive Precision Training: Quantify Back Propagation in Neural Networks with Fixed-point Numbers

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 4776–4800 of 4925 papers

TitleStatusHype
On the efficient representation and execution of deep acoustic models—0
Intra-layer Nonuniform Quantization for Deep Convolutional Neural Network—0
Random Walk Graph Laplacian based Smoothness Prior for Soft Decoding of JPEG Images—0
Adaptive Training of Random Mapping for Data Quantization—0
Fast, Compact, and High Quality LSTM-RNN Based Statistical Parametric Speech Synthesizers for Mobile Devices—0
DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth GradientsCode0
Deep neural networks are robust to weight binarization and other non-linear distortions—0
Learning Power Spectrum Maps from Quantized Power Measurements—0
Pairwise Quantization—0
Comparison of 14 different families of classification algorithms on 115 binary datasets—0
Learning compact binary descriptors with unsupervised deep neural networksCode0
Shortlist Selection With Residual-Aware Distance Estimator for K-Nearest Neighbor Search—0
Mining 3D Key-Pose-Motifs for Action Recognition—0
HyperDepth: Learning Depth From Structured Light Without Matching—0
Multilinear Hyperplane Hashing—0
Learning Compact Binary Descriptors With Unsupervised Deep Neural Networks—0
A Survey on Learning to Hash—0
TripleSpin - a generic compact paradigm for fast machine learning computations—0
A Channelized Binning Method for Extraction of Dominant Color Pixel Value—0
Composite Correlation Quantization for Efficient Multimodal Retrieval—0
Reducing the Model Order of Deep Neural Networks Using Information Theory—0
Transfer Hashing with Privileged Information—0
LOH and behold: Web-scale visual search, recommendation and clustering using Locally Optimized Hashing—0
Supervised Matrix Factorization for Cross-Modality Hashing—0
Grid Based Nonlinear Filtering Revisited: Recursive Estimation & Asymptotic Optimality—0
Show:102550
← PrevPage 192 of 197Next →
All datasetsImageNetCIFAR-10Wiki-40BAgeDB-30CFP-FPCOCO (Common Objects in Context)IJB-BIJB-CKnowledge-based:LFW

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1FQ-ViT (ViT-L)Top-1 Accuracy (%)85.03—Unverified
2FQ-ViT (ViT-B)Top-1 Accuracy (%)83.31—Unverified
3FQ-ViT (Swin-B)Top-1 Accuracy (%)82.97—Unverified
4FQ-ViT (Swin-S)Top-1 Accuracy (%)82.71—Unverified
5FQ-ViT (DeiT-B)Top-1 Accuracy (%)81.2—Unverified
6FQ-ViT (Swin-T)Top-1 Accuracy (%)80.51—Unverified
7FQ-ViT (DeiT-S)Top-1 Accuracy (%)79.17—Unverified
8Xception W8A8Top-1 Accuracy (%)78.97—Unverified
9ADLIK-MO-ResNet50-W4A4Top-1 Accuracy (%)77.88—Unverified
10ADLIK-MO-ResNet50-W3A4Top-1 Accuracy (%)77.34—Unverified
#ModelMetricClaimedVerifiedStatus
13DCNN_VIVA_3MAP160,327.04—Unverified
2DTQMAP0.79—Unverified
#ModelMetricClaimedVerifiedStatus
1OutEffHop-Bert_basePerplexity6.3—Unverified
2OutEffHop-Bert_basePerplexity6.21—Unverified
#ModelMetricClaimedVerifiedStatus
1Accuracy98.13—Unverified
#ModelMetricClaimedVerifiedStatus
1Accuracy92.92—Unverified
#ModelMetricClaimedVerifiedStatus
1SSD ResNet50 V1 FPN 640x640MAP34.3—Unverified
#ModelMetricClaimedVerifiedStatus
1TAR @ FAR=1e-495.13—Unverified
#ModelMetricClaimedVerifiedStatus
1TAR @ FAR=1e-496.38—Unverified
#ModelMetricClaimedVerifiedStatus
13DCNN_VIVA_5All84,809,664—Unverified
#ModelMetricClaimedVerifiedStatus
1Accuracy99.8—Unverified