activity
20202025
most citedComparing SNNs and RNNs on Neuromorphic Vision Datasets: Similarities and Differences

15 citations · 21 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2025

Maximizing Asynchronicity in Event-based Neural Networks

Haiqing Hao, Nikola Zubić, Weihua He +3

Event cameras deliver visual data with high temporal resolution, low latency, and minimal redundancy, yet their asynchronous, sparse sequential nature challenges standard tensor-ba…

cs.CV2022★ 2 cited

MSS-DepthNet: Depth Prediction with Multi-Step Spiking Neural Network

Xiaoshan Wu, Weihua He, Man Yao +3

Event cameras are considered to have great potential for computer vision and robotics applications because of their high temporal resolution and low power consumption characteristi…

cs.CV2022★ 3 cited

Video Interpolation by Event-driven Anisotropic Adjustment of Optical Flow

Song Wu, Kaichao You, Weihua He +5

Video frame interpolation is a challenging task due to the ever-changing real-world scene. Previous methods often calculate the bi-directional optical flows and then predict the in…

cs.CV2022★ 1 cited

TimeReplayer: Unlocking the Potential of Event Cameras for Video Interpolation

Weihua He, Kaichao You, Zhendong Qiao +6

Recording fast motion in a high FPS (frame-per-second) requires expensive high-speed cameras. As an alternative, interpolating low-FPS videos from commodity cameras has attracted s…

cs.CV2020★ 15 cited

Comparing SNNs and RNNs on Neuromorphic Vision Datasets: Similarities and Differences

Weihua He, YuJie Wu, Lei Deng +6

Neuromorphic data, recording frameless spike events, have attracted considerable attention for the spatiotemporal information components and the event-driven processing fashion. Sp…