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20222026
most citedMSS-DepthNet: Depth Prediction with Multi-Step Spiking Neural Network

2 citations · 2 across the 4 of their papers we have counts for

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cs.CV2026

OptiGeo: Efficient Monocular Geometry for Embodied Perception in Optically Challenging Scenes

Muxin Liu, Tianbo Liu, Jing Xia +7

Monocular depth estimation has achieved strong open-domain generalization, yet reliable robotic deployment remains difficult in transparent, reflective, and specular environments,…

cs.CV2026

Stabilizing Streaming Video Geometry via Dynamic Feature Normalization

Xiaoyang Lyu, Muxin Liu, Xiaoshan Wu +5

Consistent 3D geometry estimation from streaming RGB input is crucial for real-world applications such as autonomous driving, embodied AI, and large-scale reconstruction. While mod…

cs.CV2026

LiFR-Seg: Anytime High-Frame-Rate Segmentation via Event-Guided Propagation

Xiaoshan Wu, Xiaoyang Lyu, Yifei Yu +3

Dense semantic segmentation in dynamic environments is fundamentally limited by the low-frame-rate (LFR) nature of standard cameras, which creates critical perceptual gaps between…

cs.CV2025

VideoSSM: Autoregressive Long Video Generation with Hybrid State-Space Memory

Yifei Yu, Xiaoshan Wu, Xinting Hu +8

Autoregressive (AR) diffusion enables streaming, interactive long-video generation by producing frames causally, yet maintaining coherence over minute-scale horizons remains challe…

cs.CV2025

EAG3R: Event-Augmented 3D Geometry Estimation for Dynamic and Extreme-Lighting Scenes

Xiaoshan Wu, Yifei Yu, Xiaoyang Lyu +5

Robust 3D geometry estimation from videos is critical for applications such as autonomous navigation, SLAM, and 3D scene reconstruction. Recent methods like DUSt3R demonstrate that…

cs.CV20222 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…