Ngoc Anh Thai

According to our database1, Ngoc Anh Thai authored at least 13 papers between 2019 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2023
ZeroShape: Regression-based Zero-shot Shape Reconstruction.
CoRR, 2023

Low-shot Object Learning with Mutual Exclusivity Bias.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

ShapeClipper: Scalable 3D Shape Learning from Single-View Images via Geometric and CLIP-Based Consistency.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Developmental Machine Learning: From Human Learning to Machines and Back (Dagstuhl Seminar 22422).
Dagstuhl Reports, October, 2022

Learning Dense Object Descriptors from Multiple Views for Low-shot Category Generalization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Planes vs. Chairs: Category-Guided 3D Shape Learning Without any 3D Cues.
Proceedings of the Computer Vision - ECCV 2022, 2022

The Surprising Positive Knowledge Transfer in Continual 3D Object Shape Reconstruction.
Proceedings of the International Conference on 3D Vision, 2022

2021
Does Continual Learning = Catastrophic Forgetting?
CoRR, 2021

Using Shape To Categorize: Low-Shot Learning With an Explicit Shape Bias.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

3D Reconstruction of Novel Object Shapes from Single Images.
Proceedings of the International Conference on 3D Vision, 2021

2019
Virtual organelle self-coding for fluorescence imaging via adversarial learning.
CoRR, 2019

Incremental Object Learning From Contiguous Views.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Using Deep Convolutional Neural Network for Mouse Brain Segmentation in DT-MRI.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019


  Loading...