Papers with Code 아카이브

NLP based Person Retrival

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코드

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

https://github.com/multimediafor/scfnet

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Spatio-temporal Co-attention Fusion Network for Video Splicing Localization

https://github.com/multimediafor/vilocal

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Video Inpainting Localization with Contrastive Learning

https://github.com/multimedialabsfu/learned-compression-of-encoding-distributions

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Learned Compression of Encoding Distributions

https://github.com/multimodallearning/deep-geo-reg

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Deep learning based geometric registration for medical images: How accurate can we get without visual features?

https://github.com/multimodallearning/shape_matters

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Shape Matters: Detecting Vertebral Fractures Using Differentiable Point-Based Shape Decoding

https://github.com/mungomeng/survival-xsurv

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Merging-Diverging Hybrid Transformer Networks for Survival Prediction in Head and Neck Cancer

https://github.com/muqiaoy/dl_signal

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Complex Transformer: A Framework for Modeling Complex-Valued Sequence

https://github.com/mushanshanshan/esltts

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USAT: A Universal Speaker-Adaptive Text-to-Speech Approach

https://github.com/mushfiqur11/SS-VideoCaptioning

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Video captioning with stacked attention and semantic hard pull

https://github.com/mustass/ensertainty

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Decoder ensembling for learned latent geometries

https://github.com/muyeby/AMR-Backparsing

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Online Back-Parsing for AMR-to-Text Generation

https://github.com/mvme-hbut/mprlnet

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Multiple Prior Representation Learning for Self-Supervised Monocular Depth Estimation via Hybrid Transformer

https://github.com/mvme-hbut/sgacnet

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Spatial-information Guided Adaptive Context-aware Network for Efficient RGB-D Semantic Segmentation

https://github.com/mwod/sega_mw_2023

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Automatic Aorta Segmentation with Heavily Augmented, High-Resolution 3-D ResUNet: Contribution to the SEG.A Challenge

https://github.com/mxin262/estextspotter

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ESTextSpotter: Towards Better Scene Text Spotting with Explicit Synergy in Transformer

https://github.com/myinxd/dnnae-gmm

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Radio Galaxy Morphology Generation Using DNN Autoencoder and Gaussian Mixture Models

https://github.com/nachiket92/PGP

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Multimodal Trajectory Prediction Conditioned on Lane-Graph Traversals

https://github.com/nachiket92/conv-social-pooling

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Convolutional Social Pooling for Vehicle Trajectory Prediction

https://github.com/naisops/CTranS

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ConvTransSeg: A Multi-resolution Convolution-Transformer Network for Medical Image Segmentation

https://github.com/naisops/mo-ctrans

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MO-CTranS: A unified multi-organ segmentation model learning from multiple heterogeneously labelled datasets

https://github.com/namburisrinath/llmcompression

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The Cost of Compression: Investigating the Impact of Compression on Parametric Knowledge in Language Models

https://github.com/namisan/exdeep-nmt

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Very Deep Transformers for Neural Machine Translation

https://github.com/namjohn10/bidirectionalgaitnet

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Bidirectional GaitNet: A Bidirectional Prediction Model of Human Gait and Anatomical Conditions

https://github.com/namtuanly/MTL-TabNet

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An End-to-End Multi-Task Learning Model for Image-based Table Recognition

https://github.com/namtuanly/wikitableset

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Rethinking Image-based Table Recognition Using Weakly Supervised Methods

https://github.com/nandan91/relu-revival-normfree

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ReLU's Revival: On the Entropic Overload in Normalization-Free Large Language Models

https://github.com/nanjingxiaobawang/SieNet-Image-extrapolation

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SiENet: Siamese Expansion Network for Image Extrapolation

https://github.com/narcissusex/guardsplat

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GuardSplat: Efficient and Robust Watermarking for 3D Gaussian Splatting

https://github.com/narthchin/deiqt

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Data-Efficient Image Quality Assessment with Attention-Panel Decoder

https://github.com/nasa/random_field_c-lfm

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Generative Modeling of Random Fields from Limited Data via Constrained Latent Flow Matching

https://github.com/nasim-aust/braintumor-segmentation-3dunet-brats

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Brain Tumor Segmentation using Enhanced U-Net Model with Empirical Analysis

https://github.com/nathankutz/plasmashred

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Shallow Recurrent Decoder for Reduced Order Modeling of Plasma Dynamics

https://github.com/naver-ai/lut

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Learning with Unmasked Tokens Drives Stronger Vision Learners

https://github.com/naver-ai/vidt

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ViDT: An Efficient and Effective Fully Transformer-based Object Detector

https://github.com/naver/sqlova

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A Comprehensive Exploration on WikiSQL with Table-Aware Word Contextualization

https://github.com/navid-ziaei/ldgd

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A Bayesian Gaussian Process-Based Latent Discriminative Generative Decoder (LDGD) Model for High-Dimensional Data

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