https://github.com/mx-mark/dmjd
공식 코드Disjoint Masking with Joint Distillation for Efficient Masked Image Modeling
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Disjoint Masking with Joint Distillation for Efficient Masked Image Modeling
T-CNN: Tubelets with Convolutional Neural Networks for Object Detection from Videos
Object Detection from Video Tubelets with Convolutional Neural Networks
BSH-Det3D: Improving 3D Object Detection with BEV Shape Heatmap
A tomographic workflow to enable deep learning for X-ray based foreign object detection
Security Fence Inspection at Airports Using Object Detection
Object Pose Estimation using Mid-level Visual Representations
STREAMLINE: Streaming Active Learning for Realistic Multi-Distributional Settings
Local Label Point Correction for Edge Detection of Overlapping Cervical Cells
TriangleNet: Edge Prior Augmented Network for Semantic Segmentation through Cross-Task Consistency
VME: A Satellite Imagery Dataset and Benchmark for Detecting Vehicles in the Middle East and Beyond
SNIP: Single-shot Network Pruning based on Connection Sensitivity
MDHA: Multi-Scale Deformable Transformer with Hybrid Anchors for Multi-View 3D Object Detection
Cross-Domain Weakly-Supervised Object Detection through Progressive Domain Adaptation
Stable Remaster: Bridging the Gap Between Old Content and New Displays
EGTR: Extracting Graph from Transformer for Scene Graph Generation
Re-labeling ImageNet: from Single to Multi-Labels, from Global to Localized Labels
ViDT: An Efficient and Effective Fully Transformer-based Object Detector
CroCo: Self-Supervised Pre-training for 3D Vision Tasks by Cross-View Completion
SHiNe: Semantic Hierarchy Nexus for Open-vocabulary Object Detection
Task Specific Attention is one more thing you need for object detection
Fisher Information guided Purification against Backdoor Attacks
Augmented Neural Fine-Tuning for Efficient Backdoor Purification
Trainable Weight Averaging: A General Approach for Subspace Training
Warp and Learn: Novel Views Generation for Vehicles and Other Objects
UN-DETR: Promoting Objectness Learning via Joint Supervision for Unknown Object Detection
Object Detection with Pixel Intensity Comparisons Organized in Decision Trees
HoughNet: Integrating near and long-range evidence for bottom-up object detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.