https://github.com/kaidi-jin/backdoor_samples_detection
공식 코드Can We Mitigate Backdoor Attack Using Adversarial Detection Methods?
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Can We Mitigate Backdoor Attack Using Adversarial Detection Methods?
Cross-Domain Document Object Detection: Benchmark Suite and Method
K-Radar: 4D Radar Object Detection for Autonomous Driving in Various Weather Conditions
ClaimDiff: Comparing and Contrasting Claims on Contentious Issues
CAPE: Camera View Position Embedding for Multi-View 3D Object Detection
HOTR: End-to-End Human-Object Interaction Detection with Transformers
Sparse DETR: Efficient End-to-End Object Detection with Learnable Sparsity
StarGAN-VC: Non-parallel many-to-many voice conversion with star generative adversarial networks
BanMANI: A Dataset to Identify Manipulated Social Media News in Bangla
Overcoming Scene Context Constraints for Object Detection in wild using Defilters
Cylin-Painting: Seamless {360\textdegree} Panoramic Image Outpainting and Beyond
Denoising as Adaptation: Noise-Space Domain Adaptation for Image Restoration
CXMArena: Unified Dataset to benchmark performance in realistic CXM Scenarios
Is Less Really More? Fake News Detection with Limited Information
Text Simplification for Comprehension-based Question-Answering
IndoSum: A New Benchmark Dataset for Indonesian Text Summarization
Neural sentence embedding models for semantic similarity estimation in the biomedical domain
Stay Positive: Non-Negative Image Synthesis for Augmented Reality
Wiki-Reliability: A Large Scale Dataset for Content Reliability on Wikipedia
UltraFlwr -- An Efficient Federated Medical and Surgical Object Detection Framework
Benchmarking the Robustness of LiDAR-Camera Fusion for 3D Object Detection
VirTex: Learning Visual Representations from Textual Annotations
Low-Level Linguistic Controls for Style Transfer and Content Preservation
Generating Positive Bounding Boxes for Balanced Training of Object Detectors
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.