https://github.com/zongdai/autoshape
공식 코드AutoShape: Real-Time Shape-Aware Monocular 3D Object Detection
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AutoShape: Real-Time Shape-Aware Monocular 3D Object Detection
SU-SAM: A Simple Unified Framework for Adapting Segment Anything Model in Underperformed Scenes
Large-scale Evaluation of Transformer-based Article Encoders on the Task of Citation Recommendation
Paragraph-level Citation Recommendation based on Topic Sentences as Queries
Jointly RS Image Deblurring and Super-Resolution with Adjustable-Kernel and Multi-Domain Attention
Boosting Object Detection with Zero-Shot Day-Night Domain Adaptation
PointOBB-v3: Expanding Performance Boundaries of Single Point-Supervised Oriented Object Detection
Zero-Shot Aerial Object Detection with Visual Description Regularization
Mahalanobis Distance-based Multi-view Optimal Transport for Multi-view Crowd Localization
Multi-View People Detection in Large Scenes via Supervised View-Wise Contribution Weighting
MonoDETR: Depth-guided Transformer for Monocular 3D Object Detection
Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training
HPPP: Halpern-type Preconditioned Proximal Point Algorithms and Applications to Image Restoration
Cross-domain Multi-modal Few-shot Object Detection via Rich Text
Identification of Novel Classes for Improving Few-Shot Object Detection
De-coupling and De-positioning Dense Self-supervised Learning
Dynamic Label Assignment for Object Detection by Combining Predicted IoUs and Anchor IoUs
Depth-Wise Convolutions in Vision Transformers for Efficient Training on Small Datasets
ShAPO: Implicit Representations for Multi-Object Shape, Appearance, and Pose Optimization
BTS-Net: Bi-directional Transfer-and-Selection Network For RGB-D Salient Object Detection
Depth Quality-Inspired Feature Manipulation for Efficient RGB-D Salient Object Detection
Can Large Language Models Match the Conclusions of Systematic Reviews?
Universal Domain Adaptive Object Detection via Dual Probabilistic Alignment
Bifurcated backbone strategy for RGB-D salient object detection
Dynamic Scene Understanding through Object-Centric Voxelization and Neural Rendering
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.