most citedPlainMamba: Improving Non-Hierarchical Mamba in Visual Recognition

27 citations · 51 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2025

SA-EMO: Structure-Aligned Encoder Mixture of Operators for Generalizable Full-waveform Inversion

Wang Zhenyu, Li Peiyuan, Shi Yongxiang +2

Full-waveform inversion (FWI) can produce high-resolution subsurface models, yet it remains inherently ill-posed, highly nonlinear, and computationally intensive. Although recent d…

cs.RO2024★ 16 cited

RoboMIND: Benchmark on Multi-embodiment Intelligence Normative Data for Robot Manipulation

Kun Wu, Chengkai Hou, Jiaming Liu +34

In this paper, we introduce RoboMIND (Multi-embodiment Intelligence Normative Data for Robot Manipulation), a dataset containing 107k demonstration trajectories across 479 diverse…

cs.CV2024★ 7 cited

RoboMamba: Efficient Vision-Language-Action Model for Robotic Reasoning and Manipulation

Jiaming Liu, Mengzhen Liu, Zhenyu Wang +7

A fundamental objective in robot manipulation is to enable models to comprehend visual scenes and execute actions. Although existing Vision-Language-Action (VLA) models for robots…

cs.CV2024★ 1 cited

SpikeNVS: Enhancing Novel View Synthesis from Blurry Images via Spike Camera

Gaole Dai, Zhenyu Wang, Qinwen Xu +5

One of the most critical factors in achieving sharp Novel View Synthesis (NVS) using neural field methods like Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) is the…

cs.CV2024★ 27 cited

PlainMamba: Improving Non-Hierarchical Mamba in Visual Recognition

Chenhongyi Yang, Zehui Chen, Miguel Espinosa +4

We present PlainMamba: a simple non-hierarchical state space model (SSM) designed for general visual recognition. The recent Mamba model has shown how SSMs can be highly competitiv…