https://github.com/GongCheng1919/VecQ
공식 코드VecQ: Minimal Loss DNN Model Compression With Vectorized Weight Quantization
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VecQ: Minimal Loss DNN Model Compression With Vectorized Weight Quantization
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Simultaneous Image-to-Zero and Zero-to-Noise: Diffusion Models with Analytical Image Attenuation
Data Augmentation for Object Detection via Differentiable Neural Rendering
Query Adaptive Few-Shot Object Detection with Heterogeneous Graph Convolutional Networks
Avatar Knowledge Distillation: Self-ensemble Teacher Paradigm with Uncertainty
CE-Net: Context Encoder Network for 2D Medical Image Segmentation
DeRPN: Taking a further step toward more general object detection
Unsupervised Image Classification for Deep Representation Learning
FM-Fusion: Instance-aware Semantic Mapping Boosted by Vision-Language Foundation Models
Stereo R-CNN based 3D Object Detection for Autonomous Driving
Robust Region Feature Synthesizer for Zero-Shot Object Detection
Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detection
Simulating single-photon detector array sensors for depth imaging
Joint Representation of Temporal Image Sequences and Object Motion for Video Object Detection
SCSA: Exploring the Synergistic Effects Between Spatial and Channel Attention
HM-Net: A Regression Network for Object Center Detection and Tracking on Wide Area Motion Imagery
Investigating the Impact of Multi-LiDAR Placement on Object Detection for Autonomous Driving
Toward Minimal Misalignment at Minimal Cost in One-Stage and Anchor-Free Object Detection
Motion Robust High-Speed Light-Weighted Object Detection With Event Camera
Joint Viewpoint and Keypoint Estimation with Real and Synthetic Data
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.