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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/jibo27/memdeblur

공식 코드

Multi-Scale Memory-Based Video Deblurring

https://github.com/jichengyuan/cooperitive_students

공식 코드

Cooperative Students: Navigating Unsupervised Domain Adaptation in Nighttime Object Detection

https://github.com/jiechen2358/VirtualFittingRoom

공식 코드

Image-based Virtual Fitting Room

https://github.com/jimas95/CMinMax

공식 코드

cMinMax: A Fast Algorithm to Find the Corners of an N-dimensional Convex Polytope

https://github.com/jimmyma99/sarchat

공식 코드

SARChat-Bench-2M: A Multi-Task Vision-Language Benchmark for SAR Image Interpretation

https://github.com/jin-s13/unifs

공식 코드

UniFS: Universal Few-shot Instance Perception with Point Representations

https://github.com/jin-ting-he/dadeblur

공식 코드

Domain-adaptive Video Deblurring via Test-time Blurring

https://github.com/jinga-lala/damex

공식 코드

DAMEX: Dataset-aware Mixture-of-Experts for visual understanding of mixture-of-datasets

https://github.com/jinghuichen/Focused-Flip-Federated-Backdoor-Attack

공식 코드

On the Vulnerability of Backdoor Defenses for Federated Learning

https://github.com/jingy1yu/scalablemap

공식 코드

ScalableMap: Scalable Map Learning for Online Long-Range Vectorized HD Map Construction

https://github.com/jingyangcarl/LightSamplingField

공식 코드

Light Sampling Field and BRDF Representation for Physically-based Neural Rendering

https://github.com/jingyangxiang/maxq

공식 코드

MaxQ: Multi-Axis Query for N:M Sparsity Network

https://github.com/jingyi0000/bimem

공식 코드

Black-box Unsupervised Domain Adaptation with Bi-directional Atkinson-Shiffrin Memory

https://github.com/jingyunliang/rvrt

공식 코드

Recurrent Video Restoration Transformer with Guided Deformable Attention

https://github.com/jingyunliang/vrt

공식 코드

VRT: A Video Restoration Transformer

https://github.com/jingzhang617/ebmgsod

공식 코드

An Energy-Based Prior for Generative Saliency

https://github.com/jinhseo/od-wscl

공식 코드

Object Discovery via Contrastive Learning for Weakly Supervised Object Detection

https://github.com/jinlong17/advgps

공식 코드

AdvGPS: Adversarial GPS for Multi-Agent Perception Attack

https://github.com/jinlong17/bds-v2v

공식 코드

Breaking Data Silos: Cross-Domain Learning for Multi-Agent Perception from Independent Private Sources

https://github.com/jinlong17/da-detect

공식 코드

Domain Adaptive Object Detection for Autonomous Driving under Foggy Weather

https://github.com/jinlong17/v2vlc

공식 코드

Learning for Vehicle-to-Vehicle Cooperative Perception under Lossy Communication

https://github.com/jinxhy/tflexattack

공식 코드

Training-free Lexical Backdoor Attacks on Language Models

https://github.com/jinyang06/SamGOP

공식 코드

Boosting Gaze Object Prediction via Pixel-level Supervision from Vision Foundation Model

https://github.com/jinyuanli0012/pgim

공식 코드

LLMs as Bridges: Reformulating Grounded Multimodal Named Entity Recognition

https://github.com/jiwei0921/dsu

공식 코드

Promoting Saliency From Depth: Deep Unsupervised RGB-D Saliency Detection

https://github.com/jiwoogit/StyleID

공식 코드

Style Injection in Diffusion: A Training-free Approach for Adapting Large-scale Diffusion Models for Style Transfer

https://github.com/jiyuuchc/lacss

공식 코드

Point-supervised Single-cell Segmentation via Collaborative Knowledge Sharing

https://github.com/jiyuuchc/lacss_jax

공식 코드

Point-supervised Single-cell Segmentation via Collaborative Knowledge Sharing

https://github.com/jj-vice/bagm

공식 코드

BAGM: A Backdoor Attack for Manipulating Text-to-Image Generative Models

https://github.com/jjery2243542/adaptive_voice_conversion

공식 코드

One-shot Voice Conversion by Separating Speaker and Content Representations with Instance Normalization

https://github.com/jjery2243542/voice_conversion

공식 코드

Multi-target Voice Conversion without Parallel Data by Adversarially Learning Disentangled Audio Representations

https://github.com/jjhuangcs/WINNet

공식 코드

WINNet: Wavelet-inspired Invertible Network for Image Denoising

https://github.com/jjy1994/BadEncoder

공식 코드

BadEncoder: Backdoor Attacks to Pre-trained Encoders in Self-Supervised Learning

https://github.com/jkirkby3/fypy

공식 코드

Calibration and Option Pricing with Stochastic Volatility and Double Exponential Jumps

https://github.com/jkli1998/t-car

공식 코드

Zero-Shot Scene Graph Generation via Triplet Calibration and Reduction

https://github.com/jkulhanek/viewformer

공식 코드

ViewFormer: NeRF-free Neural Rendering from Few Images Using Transformers

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