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2D Classification

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코드

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

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/francesclluis/point-cloud-source-separation

공식 코드

Music source separation conditioned on 3D point clouds

https://github.com/francesclluis/source-separation-wavenet

공식 코드

End-to-end music source separation: is it possible in the waveform domain?

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/franciellevargas/FactNews

공식 코드

Predicting Sentence-Level Factuality of News and Bias of Media Outlets

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

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Wasserstein Dropout

https://github.com/fraunhofer-iis/livenvs

공식 코드

LiveNVS: Neural View Synthesis on Live RGB-D Streams

https://github.com/fraunhoferhhi/DeepCABAC

공식 코드

DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks

https://github.com/fraunhoferhhi/neural-deferred-shading

공식 코드

Multi-View Mesh Reconstruction with Neural Deferred Shading

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

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

https://github.com/freeformrobotics/eaefnet

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Explicit Attention-Enhanced Fusion for RGB-Thermal Perception Tasks

https://github.com/freestylefreelunch/freestyle

공식 코드

FreeStyle: Free Lunch for Text-guided Style Transfer using Diffusion Models

https://github.com/freesunshine0316/dep-forest-re

공식 코드

Leveraging Dependency Forest for Neural Medical Relation Extraction

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

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Unsupervised Recognition of Unknown Objects for Open-World Object Detection

https://github.com/frxxzhl/ssebt

공식 코드

Text Style Transfer Back-Translation

https://github.com/fshaik8/mismatched

공식 코드

A MISMATCHED Benchmark for Scientific Natural Language Inference

https://github.com/fsherry/non-expansive-odes

공식 코드

Designing Stable Neural Networks using Convex Analysis and ODEs

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

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

https://github.com/ftrojanattack/ftrojan

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Backdoor Attack through Frequency Domain

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

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Lighten CARAFE: Dynamic Lightweight Upsampling with Guided Reassemble Kernels

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

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

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

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Vision Transformers: From Semantic Segmentation to Dense Prediction

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

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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

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