Search Results for author:
Found 9 papers, 8 papers with code
Direct Differentiable Augmentation Search
Data augmentation has been an indispensable tool to improve the performance of deep neural networks, however the augmentation can hardly transfer among different tasks and datasets.
Learnable Graph Matching: Incorporating Graph Partitioning with Deep Feature Learning for Multiple Object Tracking
Then the association problem turns into a general graph matching between tracklet graph and detection graph.
QueryDet: Cascaded Sparse Query for Accelerating High-Resolution Small Object Detection
On the popular COCO dataset, the proposed method improves the detection mAP by 1. 0 and mAP-small by 2. 0, and the high-resolution inference speed is improved to 3. 0x on average.
1st Place Solutions of Waymo Open Dataset Challenge 2020 -- 2D Object Detection Track
In this technical report, we present our solutions of Waymo Open Dataset (WOD) Challenge 2020 - 2D Object Track.
Single Shot Neural Architecture Search Via Direct Sparse Optimization
Recently Neural Architecture Search (NAS) has aroused great interest in both academia and industry, however it remains challenging because of its huge and non-continuous search space.
SimpleDet: A Simple and Versatile Distributed Framework for Object Detection and Instance Recognition
A Simple and Versatile Framework for Object Detection and Instance Recognition
You Only Search Once: Single Shot Neural Architecture Search via Direct Sparse Optimization
Recently Neural Architecture Search (NAS) has aroused great interest in both academia and industry, however it remains challenging because of its huge and non-continuous search space.
Like What You Like: Knowledge Distill via Neuron Selectivity Transfer
In this paper, we propose a novel knowledge transfer method by treating it as a distribution matching problem.
Data-Driven Sparse Structure Selection for Deep Neural Networks
Deep convolutional neural networks have liberated its extraordinary power on various tasks.
