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2D Classification

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

https://github.com/takashiishida/irreducible

공식 코드

Is the Performance of My Deep Network Too Good to Be True? A Direct Approach to Estimating the Bayes Error in Binary Classification

https://github.com/take2rohit/poise

공식 코드

POISE: Pose Guided Human Silhouette Extraction under Occlusions

https://github.com/talkingnow/HM-Conformer

공식 코드

HM-Conformer: A Conformer-based audio deepfake detection system with hierarchical pooling and multi-level classification token aggregation methods

https://github.com/tam1032/dsaa2023-challenge-link-prediction-ds-uit_sat

공식 코드

A Text-based Approach For Link Prediction on Wikipedia Articles

https://github.com/tangshitao/quadtreeattention

공식 코드

QuadTree Attention for Vision Transformers

https://github.com/tangtaogo/lidar-nerf

공식 코드

LiDAR-NeRF: Novel LiDAR View Synthesis via Neural Radiance Fields

https://github.com/tankowa/consistencydet

공식 코드

ConsistencyDet: A Few-step Denoising Framework for Object Detection Using the Consistency Model

https://github.com/tannerbohn/AutomaticPullQuoteSelection

공식 코드

Catching Attention with Automatic Pull Quote Selection

https://github.com/tanveer-hussain/EfficientSOD

공식 코드

Densely Deformable Efficient Salient Object Detection Network

https://github.com/tanveer-hussain/efficientsod2

공식 코드

Pyramidal Attention for Saliency Detection

https://github.com/tanvirnwu/trifuse

공식 코드

LoLI-Street: Benchmarking Low-Light Image Enhancement and Beyond

https://github.com/tanyuqian/ctc-gen-eval

공식 코드

Compression, Transduction, and Creation: A Unified Framework for Evaluating Natural Language Generation

https://github.com/taokong/FoveaBox

공식 코드

FoveaBox: Beyond Anchor-based Object Detector

https://github.com/taoqi98/profairrec

공식 코드

ProFairRec: Provider Fairness-aware News Recommendation

https://github.com/taoyang1122/GradAug

공식 코드

GradAug: A New Regularization Method for Deep Neural Networks

https://github.com/taoyang1122/MutualNet

공식 코드

MutualNet: Adaptive ConvNet via Mutual Learning from Network Width and Resolution

https://github.com/taozh2017/RGBD-SODsurvey

공식 코드

RGB-D Salient Object Detection: A Survey

https://github.com/taozh2017/fapnet

공식 코드

Feature Aggregation and Propagation Network for Camouflaged Object Detection

https://github.com/taozh2017/spnet

공식 코드

Specificity-preserving RGB-D Saliency Detection

https://github.com/taozhen1110/cat-llm

공식 코드

CAT-LLM: Prompting Large Language Models with Text Style Definition for Chinese Article-style Transfer

https://github.com/tasosnent/BeyondMeSH

공식 코드

Beyond MeSH: Fine-Grained Semantic Indexing of Biomedical Literature based on Weak Supervision

https://github.com/tasosnent/MeSH_Extension

공식 코드

What is all this new MeSH about? Exploring the semantic provenance of new descriptors in the MeSH thesaurus

https://github.com/tbd-clip/efficientpose

공식 코드

ePose: Let's Make EfficientPose More Generally Applicable

https://github.com/tbrouns/eyestalker

공식 코드

Robust Video-Based Eye Tracking Using Recursive Estimation of Pupil Characteristics

https://github.com/tchittesh/fovea

공식 코드

FOVEA: Foveated Image Magnification for Autonomous Navigation

https://github.com/tdchaitanya/MMTOD

공식 코드

Borrow from Anywhere: Pseudo Multi-modal Object Detection in Thermal Imagery

https://github.com/tear-kitty/moedit

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MoEdit: On Learning Quantity Perception for Multi-object Image Editing

https://github.com/teboli/CPCR

공식 코드

End-to-end Interpretable Learning of Non-blind Image Deblurring

https://github.com/tedlentsch/union

공식 코드

UNION: Unsupervised 3D Object Detection using Object Appearance-based Pseudo-Classes

https://github.com/tejas-deo/safe-navigation-training-autonomous-vehicles-using-deep-reinforcement-learning-in-carla

공식 코드

Safe Navigation: Training Autonomous Vehicles using Deep Reinforcement Learning in CARLA

https://github.com/tencent-ailab/lodoss

공식 코드

Toward Unifying Text Segmentation and Long Document Summarization

https://github.com/tencent-ailab/season

공식 코드

Salience Allocation as Guidance for Abstractive Summarization

https://github.com/tencentarc/conmim

공식 코드

Masked Image Modeling with Denoising Contrast

https://github.com/tencentarc/t2i-adapter

공식 코드

T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models

https://github.com/tencentyouturesearch/visualrecognition-nommer

공식 코드

NomMer: Nominate Synergistic Context in Vision Transformer for Visual Recognition

https://github.com/tennine2077/pdfnet

공식 코드

Patch-Depth Fusion: Dichotomous Image Segmentation via Fine-Grained Patch Strategy and Depth Integrity-Prior

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