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Found 9 papers, 6 papers with code
ProxyBNN: Learning Binarized Neural Networks via Proxy Matrices
The matrix composed of basis vectors is referred to as the proxy matrix, and auxiliary variables serve as the coefficients of this linear combination.
Decoupling GCN with DropGraph Module for Skeleton-Based Action Recognition
Nevertheless, how to efficiently model the spatial-temporal skeleton graph without introducing extra computation burden is a challenging problem for industrial deployment.
Multi-scale Semantic Correlation Mining for Visible-Infrared Person Re-Identification
Secondly, in order to enrich the semantic information that MIMB can utilize, a quadruple-stream feature extractor (QFE) with non-shared parameters is specifically designed to extract information from different dimensions of the dataset.
SMAP: A Novel Heterogeneous Information Framework for Scenario-based Optimal Model Assignment
To address this challenge, a new problem named the Scenario-based Optimal Model Assignment (SOMA) problem is introduced and a novel framework entitled Scenario and Model Associative percepts (SMAP) is developed.
PKD: General Distillation Framework for Object Detectors via Pearson Correlation Coefficient
First, the difference in feature magnitude between the teacher and the student could enforce overly strict constraints on the student.
FedProc: Prototypical Contrastive Federated Learning on Non-IID data
In this paper, we propose FedProc: prototypical contrastive federated learning, which is a simple and effective federated learning framework.
Skeleton-Based Action Recognition With Shift Graph Convolutional Network
Instead of using heavy regular graph convolutions, our Shift-GCN is composed of novel shift graph operations and lightweight point-wise convolutions, where the shift graph operations provide flexible receptive fields for both spatial graph and temporal graph.
Ranked #3 on
Skeleton Based Action Recognition
on UAV-Human
Compact Global Descriptor for Neural Networks
Long-range dependencies modeling, widely used in capturing spatiotemporal correlation, has shown to be effective in CNN dominated computer vision tasks.
Ranked #208 on
Object Detection
on COCO test-dev
Patch Transformer for Multi-tagging Whole Slide Histopathology Images
Automated whole slide image (WSI) tagging has become a growing demand due to the increasing volume and diversity of WSIs collected nowadays in histopathology.
