Papers with Code 아카이브

Natural Language Transduction

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Converting one sequence into another

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/Fengdalu/learn-an-effective-lip-reading-model-without-pains

공식 코드

Learn an Effective Lip Reading Model without Pains

https://github.com/JackSyu/Discriminative-Multi-modality-Speech-Recognition

공식 코드

Discriminative Multi-modality Speech Recognition

https://github.com/KAIST-AILab/SyncVSR

공식 코드

SyncVSR: Data-Efficient Visual Speech Recognition with End-to-End Crossmodal Audio Token Synchronization

https://github.com/ahaliassos/lipforensics

공식 코드

Lips Don't Lie: A Generalisable and Robust Approach to Face Forgery Detection

https://github.com/ahaliassos/raven

공식 코드

Jointly Learning Visual and Auditory Speech Representations from Raw Data

https://github.com/ahaliassos/usr

공식 코드

Unified Speech Recognition: A Single Model for Auditory, Visual, and Audiovisual Inputs

https://github.com/amourwaltz/bayeslms

공식 코드

Bayesian Neural Network Language Modeling for Speech Recognition

https://github.com/david-gimeno/evaluating-end2end-spanish-lipreading

공식 코드

Evaluation of End-to-End Continuous Spanish Lipreading in Different Data Conditions

https://github.com/facebookresearch/av_hubert

공식 코드

Robust Self-Supervised Audio-Visual Speech Recognition

https://github.com/jxzhanggg/DistillAV

공식 코드

Audio-Visual Representation Learning via Knowledge Distillation from Speech Foundation Models

https://github.com/lumia-group/leveraging-self-supervised-learning-for-avsr

공식 코드

Leveraging Unimodal Self-Supervised Learning for Multimodal Audio-Visual Speech Recognition

https://github.com/mpc001/Lipreading_using_Temporal_Convolutional_Networks

공식 코드

Towards Practical Lipreading with Distilled and Efficient Models

https://github.com/mpc001/Visual_Speech_Recognition_for_Multiple_Languages

공식 코드

Visual Speech Recognition for Multiple Languages in the Wild

https://github.com/mpc001/auto_avsr

공식 코드

Auto-AVSR: Audio-Visual Speech Recognition with Automatic Labels

https://github.com/perathambkk/lipreading

공식 코드

SpotFast Networks with Memory Augmented Lateral Transformers for Lipreading

https://github.com/renqianluo/SemiNAS

공식 코드

Semi-Supervised Neural Architecture Search

https://github.com/rizkiarm/LipNet

공식 코드

LipNet: End-to-End Sentence-level Lipreading

https://github.com/rkmtlab/LipLearner

공식 코드

LipLearner: Customizable Silent Speech Interactions on Mobile Devices

https://github.com/sailordiary/deep-face-vsr

공식 코드

Can We Read Speech Beyond the Lips? Rethinking RoI Selection for Deep Visual Speech Recognition

https://github.com/sally-sh/vsp-llm

공식 코드

Where Visual Speech Meets Language: VSP-LLM Framework for Efficient and Context-Aware Visual Speech Processing

https://github.com/tstafylakis/Lipreading-ResNet

공식 코드

Combining Residual Networks with LSTMs for Lipreading

https://github.com/xing96/MIM-lipreading

공식 코드

Mutual Information Maximization for Effective Lip Reading

https://github.com/Abishalini/LipReadingGUI

LipNet: End-to-End Sentence-level Lipreading

https://github.com/Fengdalu/LipNet-PyTorch

LipNet: End-to-End Sentence-level Lipreading

https://github.com/Fengdalu/Lipreading-DenseNet3D

LRW-1000: A Naturally-Distributed Large-Scale Benchmark for Lip Reading in the Wild

https://github.com/JackSyu/AE-MSR

Discriminative Multi-modality Speech Recognition

https://github.com/LiZhenghua0311/lip

LipNet: End-to-End Sentence-level Lipreading

https://github.com/NirHeaven/D3D

LRW-1000: A Naturally-Distributed Large-Scale Benchmark for Lip Reading in the Wild

https://github.com/Oguzhanercan/Vision-Transformers

Relaxed Attention for Transformer Models

https://github.com/PatrickPrakash/LiptoSpeech

LipNet: End-to-End Sentence-level Lipreading

https://github.com/PlatDrake2875/LipNet

LipNet: End-to-End Sentence-level Lipreading

https://github.com/SMIL-SPCRAS/AVCRFormer

https://github.com/SohaibAnwaar/lip-Reading-by-Deep-learning

LipNet: End-to-End Sentence-level Lipreading

https://github.com/TIANHAO-WANG/nnstack

Learning to Transduce with Unbounded Memory

https://github.com/Yondijr/FlowerPower

Lipreading using Temporal Convolutional Networks

https://github.com/amitai1992/AutomatedLipReading

Deep Audio-Visual Speech Recognition

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.