Search Results for author:
Found 9 papers, 6 papers with code
DeFRCN: Decoupled Faster R-CNN for Few-Shot Object Detection
Few-shot object detection, which aims at detecting novel objects rapidly from extremely few annotated examples of previously unseen classes, has attracted significant research interest in the community.
Ranked #4 on
Few-Shot Object Detection
on MS-COCO (1-shot)
End-to-End Vectorized HD-map Construction with Piecewise Bezier Curve
Vectorized high-definition map (HD-map) construction, which focuses on the perception of centimeter-level environmental information, has attracted significant research interest in the autonomous driving community.
MachMap: End-to-End Vectorized Solution for Compact HD-Map Construction
This report introduces the 1st place winning solution for the Autonomous Driving Challenge 2023 - Online HD-map Construction.
PivotNet: Vectorized Pivot Learning for End-to-end HD Map Construction
Furthermore, to supervise the position and topology of the vectorized point predictions, we propose a dynamic vectorized sequence loss.
Dynamic Metric Learning: Towards a Scalable Metric Space to Accommodate Multiple Semantic Scales
%We argue that such flexibility is also important for deep metric learning, because different visual concepts indeed correspond to different semantic scales.
Ranked #2 on
Metric Learning
on DyML-Animal
Binocular Mutual Learning for Improving Few-shot Classification
From the perspective of class space on base set, existing methods either focus on utilizing all classes under a global view by normal pretraining, or pay more attention to adopt an episodic manner to train meta-tasks within few classes in a local view.
Topic words analysis based on LDA model
Our topic words analysis project is a SNA method to visualize the topic words among emails from Obama. com to accounts registered in Columbus, Ohio.
SQE: a Self Quality Evaluation Metric for Parameters Optimization in Multi-Object Tracking
We present a novel self quality evaluation metric SQE for parameters optimization in the challenging yet critical multi-object tracking task.
GRM: Gradient Rectification Module for Visual Place Retrieval
Visual place retrieval aims to search images in the database that depict similar places as the query image.
