https://github.com/cvdigitalai/katecheo
공식 코드Katecheo: A Portable and Modular System for Multi-Topic Question Answering
Papers with Code 아카이브
2D Classification
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/cvg/labelmaker
공식 코드LABELMAKER: Automatic Semantic Label Generation from RGB-D Trajectories
https://github.com/cviaai/dasha
공식 코드DASHA: Decentralized Autofocusing System with Hierarchical Agents
https://github.com/cvignac/top-n
공식 코드Top-N: Equivariant set and graph generation without exchangeability
https://github.com/cviu-csu/cr4cacd
공식 코드Exploring Contextual Relationships for Cervical Abnormal Cell Detection
https://github.com/cvlab-epfl/mvflow
공식 코드Multi-view Tracking Using Weakly Supervised Human Motion Prediction
https://github.com/cvlab-stonybrook/Weighting-Pseudo-Labels
공식 코드https://github.com/cvlab-yonsei/HVPR
공식 코드HVPR: Hybrid Voxel-Point Representation for Single-stage 3D Object Detection
https://github.com/cvmi-lab/codet
공식 코드CoDet: Co-Occurrence Guided Region-Word Alignment for Open-Vocabulary Object Detection
https://github.com/cvmi-lab/fs3d
공식 코드Prototypical VoteNet for Few-Shot 3D Point Cloud Object Detection
https://github.com/cvmi-lab/sparsekd
공식 코드Towards Efficient 3D Object Detection with Knowledge Distillation
https://github.com/cvmi-lab/syncood
공식 코드https://github.com/cxa9264/confeti
공식 코드https://github.com/cxliu0/oa-mil
공식 코드https://github.com/cxt98/ACF_perception
공식 코드Manipulation-Oriented Object Perception in Clutter through Affordance Coordinate Frames
https://github.com/cxy1997/3D_adapt_auto_driving
공식 코드Train in Germany, Test in The USA: Making 3D Object Detectors Generalize
https://github.com/cxy1997/DiffuBox
공식 코드https://github.com/cybercore-co-ltd/CoLAD
공식 코드https://github.com/cybercore-co-ltd/Single-Stage-Common-Object-Detection
공식 코드Single Stage Class Agnostic Common Object Detection: A Simple Baseline
https://github.com/cybercore-co-ltd/colad_paper
공식 코드https://github.com/cyclomon/clipstyler
공식 코드CLIPstyler: Image Style Transfer with a Single Text Condition
https://github.com/cyharyanto/llassist
공식 코드LLAssist: Simple Tools for Automating Literature Review Using Large Language Models
https://github.com/cyhuang-tw/attack-vc
공식 코드Defending Your Voice: Adversarial Attack on Voice Conversion
https://github.com/cyjie429/rego
공식 코드Region-Based Optimization in Continual Learning for Audio Deepfake Detection
https://github.com/cylance/perturbed-sequence-model
공식 코드PROPS: Probabilistic personalization of black-box sequence models
https://github.com/cyprienquemeneur/fedpylot
공식 코드FedPylot: Navigating Federated Learning for Real-Time Object Detection in Internet of Vehicles
https://github.com/cz26/cycletransgan-evc
공식 코드CycleTransGAN-EVC: A CycleGAN-based Emotional Voice Conversion Model with Transformer
https://github.com/czczup/URST
공식 코드Towards Ultra-Resolution Neural Style Transfer via Thumbnail Instance Normalization
https://github.com/czczup/block-shuffle
공식 코드Block Shuffle: A Method for High-resolution Fast Style Transfer with Limited Memory
https://github.com/czczup/vit-adapter
공식 코드https://github.com/czhang0528/MosaicOS
공식 코드MosaicOS: A Simple and Effective Use of Object-Centric Images for Long-Tailed Object Detection
https://github.com/czm369/mixpl
공식 코드https://github.com/d-li14/HBONet
공식 코드https://github.com/d-robotics-ai-lab/dosod
공식 코드https://github.com/dachunkai/ev-deblurvsr
공식 코드https://github.com/dada-bots/dadaGP
공식 코드DadaGP: A Dataset of Tokenized GuitarPro Songs for Sequence Models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.