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Found 9 papers, 1 papers with code
Distilling Temporal Knowledge with Masked Feature Reconstruction for 3D Object Detection
Ultimately, we utilize this reconstruction target to reconstruct the student features.
BEV-LaneDet: An Efficient 3D Lane Detection Based on Virtual Camera via Key-Points
Experimental results demonstrate that our work outperforms the state-of-the-art approaches in terms of F-Score, being 10. 6% higher on the OpenLane dataset and 4. 0% higher on the Apollo 3D synthetic dataset, with a speed of 185 FPS.
BEV-LaneDet: a Simple and Effective 3D Lane Detection Baseline
Experimental results demonstrate that our work outperforms the state-of-the-art approaches in terms of F-Score, being 10. 6% higher on the OpenLane dataset and 5. 9% higher on the Apollo 3D synthetic dataset, with a speed of 185 FPS.
Ranked #1 on
3D Lane Detection
on Apollo Synthetic 3D Lane
Domain Balancing: Face Recognition on Long-Tailed Domains
Finally, we propose a Domain Balancing Margin (DBM) in the loss function to further optimize the feature space of the tail domains to improve generalization.
Learning Meta Face Recognition in Unseen Domains
Face recognition systems are usually faced with unseen domains in real-world applications and show unsatisfactory performance due to their poor generalization.
Cross-Enhancement Transform Two-Stream 3D ConvNets for Action Recognition
In this way, the enhanced-trained stream and teacher stream are combined to infer actions.
Bypass Enhancement RGB Stream Model for Pedestrian Action Recognition of Autonomous Vehicles
Pedestrian action recognition and intention prediction is one of the core issues in the field of autonomous driving.
Action Recognition in Untrimmed Videos with Composite Self-Attention Two-Stream Framework
This model can implement action recognition under zero-shot conditions, and has good recognition performance for untrimmed video data.
A Novel Task-Oriented Text Corpus in Silent Speech Recognition and its Natural Language Generation Construction Method
In the process of construction, we propose a task-oriented hybrid construction method based on natural language generation algorithm.
