https://github.com/yaqingwang/WeFEND-AAAI20
공식 코드Weak Supervision for Fake News Detection via Reinforcement Learning
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Weak Supervision for Fake News Detection via Reinforcement Learning
Flow Priors for Linear Inverse Problems via Iterative Corrupted Trajectory Matching
One-shot Unsupervised Domain Adaptation with Personalized Diffusion Models
Mix and match networks: encoder-decoder alignment for zero-pair image translation
Exact Feature Distribution Matching for Arbitrary Style Transfer and Domain Generalization
Point-DAE: Denoising Autoencoders for Self-supervised Point Cloud Learning
Weakly Supervised Object Detection for Automatic Tooth-marked Tongue Recognition
Deep Learning-based approaches for automatic detection of shell nouns and evaluation on WikiText-2
STCMOT: Spatio-Temporal Cohesion Learning for UAV-Based Multiple Object Tracking
SCTc-TE: A Comprehensive Formulation and Benchmark for Temporal Event Forecasting
Restoring Real-World Degraded Events Improves Deblurring Quality
Cap2Det: Learning to Amplify Weak Caption Supervision for Object Detection
Knowledge-guided Open Attribute Value Extraction with Reinforcement Learning
Learning to Aggregate Multi-Scale Context for Instance Segmentation in Remote Sensing Images
Isometric Transformation Invariant and Equivariant Graph Convolutional Networks
Generating Band-Limited Adversarial Surfaces Using Neural Networks
EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything
Uncertainty-aware Contrastive Distillation for Incremental Semantic Segmentation
FemtoDet: An Object Detection Baseline for Energy Versus Performance Tradeoffs
GMT: Enhancing Generalizable Neural Rendering via Geometry-Driven Multi-Reference Texture Transfer
Entropy Loss: An Interpretability Amplifier of 3D Object Detection Network for Intelligent Driving
Eloss in the way: A Sensitive Input Quality Metrics for Intelligent Driving
AVS-Net: Point Sampling with Adaptive Voxel Size for 3D Scene Understanding
Few-Shot Object Detection via Association and DIscrimination
BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction
V-DETR: DETR with Vertex Relative Position Encoding for 3D Object Detection
Spatio-temporal Self-Supervised Representation Learning for 3D Point Clouds
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.