most citedIn the Blink of an Eye: Event-based Emotion Recognition

21 citations · 36 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV20232 cited

A Geometrical Approach to Evaluate the Adversarial Robustness of Deep Neural Networks

Yang Wang, Bo Dong, Ke Xu +4

Deep Neural Networks (DNNs) are widely used for computer vision tasks. However, it has been shown that deep models are vulnerable to adversarial attacks, i.e., their performances d…

cs.GR202321 cited

In the Blink of an Eye: Event-based Emotion Recognition

Haiwei Zhang, Jiqing Zhang, Bo Dong +5

We introduce a wearable single-eye emotion recognition device and a real-time approach to recognizing emotions from partial observations of an emotion that is robust to changes in…

cs.RO20232 cited

Event-Enhanced Multi-Modal Spiking Neural Network for Dynamic Obstacle Avoidance

Yang Wang, Bo Dong, Yuji Zhang +4

Autonomous obstacle avoidance is of vital importance for an intelligent agent such as a mobile robot to navigate in its environment. Existing state-of-the-art methods train a spiki…

cs.CL20231 cited

APAM: Adaptive Pre-training and Adaptive Meta Learning in Language Model for Noisy Labels and Long-tailed Learning

Sunyi Chi, Bo Dong, Yiming Xu +2

Practical natural language processing (NLP) tasks are commonly long-tailed with noisy labels. Those problems challenge the generalization and robustness of complex models such as D…

cs.CV202310 cited

Head-Free Lightweight Semantic Segmentation with Linear Transformer

Bo Dong, Pichao Wang, Fan Wang

Existing semantic segmentation works have been mainly focused on designing effective decoders; however, the computational load introduced by the overall structure has long been ign…

cs.CV2021

All You Need is RAW: Defending Against Adversarial Attacks with Camera Image Pipelines

Yuxuan Zhang, Bo Dong, Felix Heide

Existing neural networks for computer vision tasks are vulnerable to adversarial attacks: adding imperceptible perturbations to the input images can fool these methods to make a fa…