Yajing Zheng

Orcid: 0000-0002-6355-7354

According to our database1, Yajing Zheng authored at least 28 papers between 2018 and 2026.

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

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
SNNTracker: Online High-Speed Multi-Object Tracking With Spike Camera.
IEEE Trans. Pattern Anal. Mach. Intell., January, 2026

Just Noticeable Difference Modeling for Deep Visual Features.
CoRR, January, 2026

VISTA-3D : Training-free unfolding for vision-based 3D object detection.
Neural Networks, 2026

SpikeCV: open a continuous computer vision era.
Sci. China Inf. Sci., 2026

2025
SpikeDerain: Unveiling Clear Videos from Rainy Sequences Using Color Spike Streams.
CoRR, March, 2025

Rethinking High-speed Image Reconstruction Framework with Spike Camera.
CoRR, January, 2025

Spike Camera Image Reconstruction Based on an Efficient Spiking Transformer.
Proceedings of the MMAsia '25 Workshops: Proceedings of the 7th ACM International Conference on Multimedia in Asia, 2025

USP-Gaussian: Unifying Spike-based Image Reconstruction, Pose Correction and Gaussian Splatting.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

Rethinking High-speed Image Reconstruction Framework with Spike Camera.
Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024
SpikeMM: Flexi-Magnification of High-Speed Micro-Motions.
CoRR, 2024

Continuous Spatiotemporal Events Decoupling through Spike-based Bayesian Computation.
Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

SpikeReveal: Unlocking Temporal Sequences from Real Blurry Inputs with Spike Streams.
Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

SpikeGS: 3D Gaussian Splatting from Spike Streams with High-Speed Camera Motion.
Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

Spike-guided Motion Deblurring with Unknown Modal Spatiotemporal Alignment.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Transient Glimpses: Unveiling Occluded Backgrounds through the Spike Camera.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Capture the Moment: High-Speed Imaging With Spiking Cameras Through Short-Term Plasticity.
IEEE Trans. Pattern Anal. Mach. Intell., July, 2023

Spike-Based Motion Estimation for Object Tracking Through Bio-Inspired Unsupervised Learning.
IEEE Trans. Image Process., 2023

Unveiling the Potential of Spike Streams for Foreground Occlusion Removal from Densely Continuous Views.
CoRR, 2023

SpikeCV: Open a Continuous Computer Vision Era.
CoRR, 2023

Enhancing Motion Deblurring in High-Speed Scenes with Spike Streams.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Revealing Fine Structures of the Retinal Receptive Field by Deep-Learning Networks.
IEEE Trans. Cybern., 2022

1000x Faster Camera and Machine Vision with Ordinary Devices.
CoRR, 2022

2021
Unraveling neural coding of dynamic natural visual scenes via convolutional recurrent neural networks.
Patterns, 2021

High-Speed Image Reconstruction Through Short-Term Plasticity for Spiking Cameras.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020
Probabilistic inference of binary Markov random fields in spiking neural networks through mean-field approximation.
Neural Networks, 2020

Reconstruction of natural visual scenes from neural spikes with deep neural networks.
Neural Networks, 2020

2019
Reconstruction of Natural Visual Scenes from Neural Spikes with Deep Neural Networks.
CoRR, 2019

2018
Sparse Temporal Encoding of Visual Features for Robust Object Recognition by Spiking Neurons.
IEEE Trans. Neural Networks Learn. Syst., 2018


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