activity
20202026
most citedPRIOR: Personalized Prior for Reactivating the Information Overlooked in Federated Learning

5 citations · 9 across the 16 of their papers we have counts for

collaborators
Showing cs.CVShow all

6 papers · 1 filter

cs.CV2026

Spatial-Aware Reduction Framework: Towards Efficient and Faithful Visual State Space Models

Jindi Lv, Aoyu Li, Yuhao Zhou +6

Mamba demonstrates strong efficiency in modeling long visual sequences. However, when token reduction is applied to structurally enhanced Mamba variants, these models exhibit a sev…

cs.CV2026

ForgeVLA: Federated Vision-Language-Action Learning without Language Annotations

Yuhao Zhou, Yunpeng Zhu, Yang Zhou +7

Vision-Language-Action (VLA) models hold great promise for general-purpose robotic intelligence, yet scaling up such models is severely bottlenecked by the high cost of acquiring a…

cs.CV2025

GPS: Distilling Compact Memories via Grid-based Patch Sampling for Efficient Online Class-Incremental Learning

Mingchuan Ma, Yuhao Zhou, Jindi Lv +5

Online class-incremental learning aims to enable models to continuously adapt to new classes with limited access to past data, while mitigating catastrophic forgetting. Replay-base…

cs.CV2024

Faster Vision Mamba is Rebuilt in Minutes via Merged Token Re-training

Mingjia Shi, Yuhao Zhou, Ruiji Yu +8

Vision Mamba has shown close to state of the art performance on computer vision tasks, drawing much interest in increasing it's efficiency. A promising approach is token reduction…

cs.CV2022

Fuse Local and Global Semantics in Representation Learning

Yuchi Zhao, Yuhao Zhou

We propose Fuse Local and Global Semantics in Representation Learning (FLAGS) to generate richer representations. FLAGS aims at extract both global and local semantics from images…

cs.CV2020

Learning to Simulate Dynamic Environments with GameGAN

Seung Wook Kim, Yuhao Zhou, Jonah Philion +2

Simulation is a crucial component of any robotic system. In order to simulate correctly, we need to write complex rules of the environment: how dynamic agents behave, and how the a…