arXiv:2606. 00121v1 Announce Type: cross Abstract: Reconstructing visual stimuli from brain recordings has been a meaningful and challenging task in brain decoding.
By Yizhuo Lu, Changde Du, Qiongyi Zhou, Liuyun Jiang, Huiguang He
arXiv:2607. 13421v1 Announce Type: cross Abstract: Spatio-Temporal Video Grounding (STVG) aims to retrieve the visual trajectory of a specific object from a video stream as described by a natural language expression.
By Kai Chen, Ming Dai, Wenxuan Cheng, Wankou Yang
S3VD is a new video deraining framework that leverages semantic guidance and spatio‑temporal scanning to improve performance over existing State Space Models such as Mamba. It introduces a Multi‑Scale Semantic Fusion module that uses DINOv2 priors to preserve 2D spatial semantics, and a Spatio‑Temporal Scanning Fusion module that incorporates a Decoupled‑Gating Mamba layer to better model intra‑ and inter‑frame correlations. Experiments on video deraining benchmarks show that S3VD achieves state‑of‑the‑art results, improving PSNR by an average of 0.84 dB over Mamba‑based baselines.
By Kui Jiang, Yiang Chen, Yan Luo, Zhaocheng Yu, Junjun Jiang, Xianming Liu
arXiv:2606. 14765v1 Announce Type: cross Abstract: Self-supervised video representation learning has recently advanced through contrastive learning, masked reconstruction, and predictive representation learning.
By Qinwu Xu
arXiv:2607. 18344v1 Announce Type: cross Abstract: EEG-based visual decoding provides a non-invasive pathway for interpreting visual semantics.
By Yiheng Liu, Chuhang Zheng, Peiliang Gong, Jingtao Liu, Daoqiang Zhang, Qi Zhu
arXiv:2607. 18344v2 Announce Type: replace-cross Abstract: EEG-based visual decoding provides a non-invasive pathway for interpreting visual semantics.
By Yiheng Liu, Chuhang Zheng, Peiliang Gong, Jingtao Liu, Daoqiang Zhang, Qi Zhu