5 papers
Optimizing Multi-Modality Trackers via Significance-Regularized Tuning
Zhiwen Chen, Jinjian Wu, Zhiyu Zhu +3
This paper tackles the critical challenge of optimizing multi-modality trackers by effectively adapting pre-trained models for RGB data. Existing fine-tuning paradigms oscillate be…
Scaling Dense Event-Stream Pretraining from Visual Foundation Models
Zhiwen Chen, Junhui Hou, Zhiyu Zhu +2
Learning versatile, fine-grained representations from irregular event streams is pivotal yet nontrivial, primarily due to the heavy annotation that hinders scalability in dataset s…
Self-supervised Learning of LiDAR 3D Point Clouds via 2D-3D Neural Calibration
Yifan Zhang, Junhui Hou, Siyu Ren +3
This paper introduces a novel self-supervised learning framework for enhancing 3D perception in autonomous driving scenes. Specifically, our approach, namely NCLR, focuses on 2D-3D…
An O(m+n)-Space Spatiotemporal Denoising Filter with Cache-Like Memories for Dynamic Vision Sensors
Qinghang Zhao, Jiaqi Wang, Yixi Ji +2
Dynamic vision sensor (DVS) is novel neuromorphic imaging device that generates asynchronous events. Despite the high temporal resolution and high dynamic range features, DVS is fa…
E-Motion: Future Motion Simulation via Event Sequence Diffusion
Song Wu, Zhiyu Zhu, Junhui Hou +2
Forecasting a typical object's future motion is a critical task for interpreting and interacting with dynamic environments in computer vision. Event-based sensors, which could capt…