activity
20242026
collaborators

12 papers

cs.CV2026

Splats in Splats++: Robust and Generalizable 3D Gaussian Splatting Steganography

Yijia Guo, Wenkai Huang, Tong Hu +9

3D Gaussian Splatting (3DGS) has recently redefined the paradigm of 3D reconstruction, striking an unprecedented balance between visual fidelity and computational efficiency. As it…

cs.NE2026

Spike-driven Large Language Model

Han Xu, Xuerui Qiu, Baiyu Chen +7

Current Large Language Models (LLMs) are primarily based on large-scale dense matrix multiplications. Inspired by the brain's information processing mechanism, we explore the funda…

cs.NE2026

GemS-T: Multi-Dimensional Grouping for Ultra-High Energy Efficiency in Spiking Transformer

Zecheng Hao, Shenghao Xie, Kang Chen +3

Spiking Neural Networks (SNNs) offer superior energy efficiency over Artificial Neural Networks (ANNs). However, they encounter significant deficiencies in training and inference m…

cs.CV2026

Can Protective Watermarking Safeguard the Copyright of 3D Gaussian Splatting?

Wenkai Huang, Yijia Guo, Gaolei Li +6

3D Gaussian Splatting (3DGS) has emerged as a powerful representation for 3D scenes, widely adopted due to its exceptional efficiency and high-fidelity visual quality. Given the si…

q-bio.NC2026

Retina gap junctions support the robust perception by warping neural representational geometries along the visual hierarchy

Yang Yue, Shenjian Zhang, Yonghong Tian +2

Deep Neural Networks (DNNs) are vulnerable to elaborately designed adversarial noise, although they have achieved extraordinary success in many tasks. Compared with DNNs, the human…

cs.CV2025

On-the-fly Large-scale 3D Reconstruction from Multi-Camera Rigs

Yijia Guo, Tong Hu, Zhiwei Li +6

Recent advances in 3D Gaussian Splatting (3DGS) have enabled efficient free-viewpoint rendering and photorealistic scene reconstruction. While on-the-fly extensions of 3DGS have sh…