Papers with Code 아카이브

16k

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

6

평가표

1

보존된 평가 기록

1

코드

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

https://github.com/flyegle/sdwnet

공식 코드

SDWNet: A Straight Dilated Network with Wavelet Transformation for Image Deblurring

https://github.com/fnozarian/ReliableStudent

공식 코드

Reliable Student: Addressing Noise in Semi-Supervised 3D Object Detection

https://github.com/fod-unomaha/fodanomalydata

공식 코드

Foreign Object Debris Detection for Airport Pavement Images based on Self-supervised Localization and Vision Transformer

https://github.com/forAcadamic/T-CAD

공식 코드

TAD: A Large-Scale Benchmark for Traffic Accidents Detection from Video Surveillance

https://github.com/fordevoted/uiess

공식 코드

Domain Adaptation for Underwater Image Enhancement via Content and Style Separation

https://github.com/forresti/caffe

공식 코드

DenseNet: Implementing Efficient ConvNet Descriptor Pyramids

https://github.com/foundationvision/generateu

공식 코드

Generative Region-Language Pretraining for Open-Ended Object Detection

https://github.com/fpv-iplab/DA-RetinaNet

공식 코드

An Unsupervised Domain Adaptation Scheme for Single-Stage Artwork Recognition in Cultural Sites

https://github.com/fpv-iplab/MECCANO

공식 코드

The MECCANO Dataset: Understanding Human-Object Interactions from Egocentric Videos in an Industrial-like Domain

https://github.com/fpv-iplab/STMDA-RetinaNet

공식 코드

A Multi Camera Unsupervised Domain Adaptation Pipeline for Object Detection in Cultural Sites through Adversarial Learning and Self-Training

https://github.com/francescocappio/oshot-meta-learning

공식 코드

Self-Supervision & Meta-Learning for One-Shot Unsupervised Cross-Domain Detection

https://github.com/franchesoni/iadet

공식 코드

IAdet: Simplest human-in-the-loop object detection

https://github.com/francis0625/omni-sr

공식 코드

Omni Aggregation Networks for Lightweight Image Super-Resolution

https://github.com/franciszzj/openpsg

공식 코드

OpenPSG: Open-set Panoptic Scene Graph Generation via Large Multimodal Models

https://github.com/frankfengdi/LidarMTL

공식 코드

A Simple and Efficient Multi-task Network for 3D Object Detection and Road Understanding

https://github.com/fraunhofer-iais/second-moment-loss

공식 코드

Wasserstein Dropout

https://github.com/fraunhoferiks/smf-object-detection

공식 코드

Preventing Errors in Person Detection: A Part-Based Self-Monitoring Framework

https://github.com/freeformrobotics/eaefnet

공식 코드

Explicit Attention-Enhanced Fusion for RGB-Thermal Perception Tasks

https://github.com/fregu856/ebms_3dod

공식 코드

Accurate 3D Object Detection using Energy-Based Models

https://github.com/fregu856/ebms_regression

공식 코드

Energy-Based Models for Deep Probabilistic Regression

https://github.com/freshn/anti-aliasing-tiny-object-detection

공식 코드

The Importance of Anti-Aliasing in Tiny Object Detection

https://github.com/frezaeix/VISGA_Public

공식 코드

Seeking Similarities over Differences: Similarity-based Domain Alignment for Adaptive Object Detection

https://github.com/frh23333/mepu-owod

공식 코드

Unsupervised Recognition of Unknown Objects for Open-World Object Detection

https://github.com/fried-rice-lab/emt

공식 코드

Efficient Mixed Transformer for Single Image Super-Resolution

https://github.com/fried-rice-lab/friedricelab

공식 코드

Image Super-Resolution using Efficient Striped Window Transformer

https://github.com/frozenburning/scenedreamer

공식 코드

SceneDreamer: Unbounded 3D Scene Generation from 2D Image Collections

https://github.com/fsod/cd-fsod

공식 코드

CD-FSOD: A Benchmark for Cross-domain Few-shot Object Detection

https://github.com/fu0511/dynamic-lightweight-upsampling

공식 코드

Lighten CARAFE: Dynamic Lightweight Upsampling with Guided Reassemble Kernels

https://github.com/fudan-zvg/Brain3D

공식 코드

Brain3D: Generating 3D Objects from fMRI

https://github.com/fudan-zvg/DDMP

공식 코드

Depth-conditioned Dynamic Message Propagation for Monocular 3D Object Detection

https://github.com/fudan-zvg/SETR

공식 코드

Vision Transformers: From Semantic Segmentation to Dense Prediction

https://github.com/fudan-zvg/deepinteraction

공식 코드

DeepInteraction: 3D Object Detection via Modality Interaction

https://github.com/fudan-zvg/dgmn2

공식 코드

Dynamic Graph Message Passing Networks

https://github.com/fudan-zvg/ego3rt

공식 코드

Learning Ego 3D Representation as Ray Tracing

https://github.com/fudan-zvg/partner

공식 코드

PARTNER: Level up the Polar Representation for LiDAR 3D Object Detection

https://github.com/fudan-zvg/polarformer

공식 코드

PolarFormer: Multi-camera 3D Object Detection with Polar Transformer

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