IEEE TPAMI

Toward Visual Grounding: A Survey

视觉定位：一项综述

Linhui Xiao, Xiaoshan Yang, Xiangyuan Lan, Yaowei Wang, Changsheng Xu

AI总结 本综述梳理视觉定位的发展与背景，总结近年进展与新挑战，定义规范研究设置，介绍相关数据集与应用，提出未来方向，是该领域最全面的综述，适合不同阶段研究者。

Comments Accepted by TPAMI 2025. We keep tracing related works at https://github.com/linhuixiao/Awesome-Visual-Grounding, article publication page: https://ieeexplore.ieee.org/abstract/document/11235566

Journal ref IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 48, no. 3, pp. 2749-2771, March 2026

Adversarial Purification by Consistency-aware Latent Space Optimization on Data Manifolds

基于数据流形上感知一致性隐空间优化的对抗净化

Shuhai Zhang, Jiahao Yang, Hui Luo, Jie Chen, Li Wang, Feng Liu, Bo Han, Mingkui Tan

AI总结 针对对抗净化易过度校正的问题，提出CMAP方法，通过在一致性模型隐空间优化向量恢复干净数据，在CIFAR-10和ImageNet-100上提升了对抗鲁棒性与自然准确率。

Comments Accepted at TPAMI 2026

Multi-Camera Trajectory Forecasting with Trajectory Tensors

基于轨迹张量的多摄像头轨迹预测

Olly Styles, Tanaya Guha, Victor Sanchez

AI总结 该研究针对多摄像头轨迹预测（MCTF）问题，提出轨迹张量技术及对应编码器-解码器模型，在含15个摄像头视角600小时视频的自建数据库上验证，其模型性能优于现有相关方法。

Comments To appear in IEEE Transactions on Pattern Analysis and Machine Intelligence (tPAMI)