Search Results for author:
Found 5 papers, 1 papers with code
Revisiting Architecture-aware Knowledge Distillation: Smaller Models and Faster Search
Knowledge Distillation (KD) has recently emerged as a popular method for compressing neural networks.
End-to-End Lane Marker Detection via Row-wise Classification
In autonomous driving, detecting reliable and accurate lane marker positions is a crucial yet challenging task.
Ranked #19 on
Lane Detection
on TuSimple
Fine-Grained Neural Architecture Search
We present an elegant framework of fine-grained neural architecture search (FGNAS), which allows to employ multiple heterogeneous operations within a single layer and can even generate compositional feature maps using several different base operations.
SeedNet: Automatic Seed Generation With Deep Reinforcement Learning for Robust Interactive Segmentation
In this paper, we propose an automatic seed generation technique with deep reinforcement learning to solve the interactive segmentation problem.
Tensor-Based High-Order Semantic Relation Transfer for Semantic Scene Segmentation
In this paper, we propose semantic relation transfer, a method to transfer high-order semantic relations of objects from annotated images to unlabeled images analogous to label transfer techniques where label information are transferred.
