Publications论文

Ten papers, 2025–2026. 十篇论文,2025—2026。

Peer-reviewed journal and conference papers, ordered by year. * marks the corresponding author; † marks equal contribution. A BibTeX entry is provided for every paper.

按年份排列的期刊与会议论文。* 表示通讯作者,† 表示共同第一作者。每篇论文均提供 BibTeX 条目。

Peer-reviewed同行评审

Journal and conference papers.期刊与会议论文。

Filter筛选
2026

Gauge-Equivariant Attention for Rotation-Stable 360° Scene Understanding (EquiSSL)

Tianjian Zhou, Yishan Li, Jie Jiang*, Yifei Zhang

ACM Transactions on Graphics, Vol. 45, No. 6, Article 242 · SIGGRAPH Asia 2026 Journal Track

CCF-AACM TOGSIGGRAPH Asia '26

TL;DR — Spherical transformers lose more than half their segmentation accuracy when the camera rotates by 90°. EquiSSL removes the gauge dependence of the attention bias with a parameter-free Reynolds average, cutting that drop to 0.8% and turning rotation-consistent self-supervision into a label-efficiency lever.

一句话总结——球面 Transformer 在相机旋转 90° 时会损失过半的分割精度。EquiSSL 以无参数的 Reynolds 平均消除注意力偏置的规范依赖,将精度下降降至 0.8%,并把旋转一致的自监督变成提升标签效率的杠杆。

2026

DAGA: Dynamic Attention-Guided Adaptation for Self-Supervised Vision Transformers

Tianjian Zhou†, Jie Jiang†, Yishan Li*, Yifei Zhang*

Advances in Neural Information Processing Systems (NeurIPS 2026)

CCF-ANeurIPS

TL;DR — A dynamic, parameter-efficient adapter for frozen self-supervised ViTs, which uses attention guidance to select the features a downstream task needs and achieves strong transfer across benchmarks.

一句话总结——面向冻结自监督 ViT 的动态参数高效适配器,通过注意力引导选择下游任务所需的特征,在多个基准上取得出色的迁移表现。

2026

Less Is More: Minimal Components for Contrastive Learning Delivering Superior Accuracy and Efficiency (CORE)

Tianjian Zhou, Yishan Li, Lixin Zhan, Jie Jiang*

IEEE Transactions on Neural Networks and Learning Systems, 2026

CCF-BCAS Tier 1中科院一区IEEE TNNLS

TL;DR — A systematic deconstruction of modern contrastive frameworks shows that momentum encoders and deep projection heads are not necessary: removing them cuts training compute by 42% while improving linear-probe accuracy.

一句话总结——对现代对比学习框架的系统性拆解表明,动量编码器与深层投影头并非必要:去掉它们可减少 42% 的训练计算量,同时提升线性探针精度。

2026

Semantic-Guided Data Augmentation for Self-Supervised Visual Pattern Learning: Leveraging Foundation Model Priors (SDI)

Tianjian Zhou, Jie Jiang*, Yishan Li, Lixin Zhan, Rui Qi, Liang Bai

Pattern Recognition, Vol. 160, 2026

CCF-BCAS Tier 1中科院一区Pattern Recognition

TL;DR — Semantic Data Inflation uses diffusion foundation-model priors to generate semantically consistent counterfactual views, avoiding both the semantic damage of random transformations and the drift of unconstrained generative augmentation.

一句话总结——Semantic Data Inflation 借助扩散基础模型先验生成语义一致的反事实视图,既避免随机变换对语义的破坏,也避免无约束生成增广带来的语义漂移。

2026

HTNet: A Self-Supervised Heterogeneous Triple Network for Multi-Modal Data

Tianjian Zhou, Yishan Li, Lixin Zhan, Jie Jiang*

Neural Networks, Vol. 178, 2026

CCF-BNeural Networks

TL;DR — A heterogeneous triple network for unaligned multi-modal data, which handles asymmetric cross-modal information without requiring paired annotations across modalities.

一句话总结——面向未对齐多模态数据的异构三重网络,无需跨模态配对标注即可处理非对称的跨模态信息。

2026

CMAE: Contrastive Manifold Autoencoder for Efficient Latent Diffusion

Tianjian Zhou*†, Yishan Li*†, Jie Jiang†*, Liang Bai, Yifei Zhang

IEEE International Conference on Multimedia and Expo (ICME 2026) · Oral

CCF-BIEEE ICME 2026Oral口头报告

TL;DR — Replaces the standard VAE latent space with contrastive manifold autoencoding, preserving high-frequency edges and semantic structure and accelerating diffusion sampling by 2.1×.

一句话总结——以对比流形自编码替代标准 VAE 潜在空间,保留高频边缘与语义结构,并把扩散采样速度提升 2.1 倍。

2026

P-SLCR: Unsupervised Point Cloud Semantic Segmentation via Prototypes Structure Learning and Consistent Reasoning

Lixin Zhan, Jie Jiang*, Tianjian Zhou, Yukun Du, Yan Zheng, Xuehu Duan

AAAI Conference on Artificial Intelligence (AAAI 2026)

CCF-AAAAI

TL;DR — Unsupervised point cloud semantic segmentation through prototype topology discovery and consistent spatial-geometric reasoning, without any point-level annotations.

一句话总结——通过原型拓扑发现与一致的空间几何推理实现无监督点云语义分割,无需任何点级标注。

2026

BGC-Net: Bilateral Graph Convolutional Network for Weakly Supervised Semantic Segmentation of Large-Scale Point Clouds

Lixin Zhan, Yukun Du, Jie Jiang*, Yingmei Wei, Tianjian Zhou, Ziyuan Yang

IEEE Transactions on Circuits and Systems for Video Technology, Vol. 36, No. 3, 2026

CCF-BIEEE TCSVT

TL;DR — Bilateral graph convolutions extract informative spatial representations from sparse point annotations, making large-scale 3D point cloud parsing feasible under weak supervision.

一句话总结——双边图卷积从稀疏点标注中提取有信息量的空间表示,使弱监督下的大规模三维点云解析成为可能。

2026

TriCM-Net: Triple Cross-Modal Interaction for Infrared–Visible Abnormal Behavior Recognition

Jie Jiang*, Tianjian Zhou†, Yishan Li†

Chinese Conference on Pattern Recognition and Computer Vision (PRCV 2026)

CCF-CPRCV 2026

TL;DR — Triple cross-modal interaction exploits the complementary strengths of infrared localization and visible texture for round-the-clock abnormal behavior recognition.

一句话总结——三重跨模态交互利用红外的定位能力与可见光的纹理信息,实现全天候的异常行为识别。

2025

QPCR: Weakly Supervised Semantic Segmentation of Large-Scale Point Cloud via Gradual Query Points Component Reasoning

Lixin Zhan, Wei Li, Jie Jiang*, Tianjian Zhou, Chenglu Wen, Cheng Wang

IEEE Transactions on Geoscience and Remote Sensing, Vol. 63, 2025

JCR Q1IEEE TGRS

TL;DR — Component-wise iterative reasoning for large-scale terrain point clouds, which recovers reliable segmentation under sparse ground-truth supervision.

一句话总结——面向大规模地形点云的分量式迭代推理,在稀疏真值监督下恢复可靠的分割结果。

Patents专利

Four granted invention patents.四项授权发明专利。

Academic service学术服务

Image feature extraction method based on a self-supervised triple neural network 基于自监督三重神经网络的图像特征提取方法

National invention patent · inventors Jie Jiang, Tianjian Zhou (2nd inventor), Yishan Li, et al. 国家发明专利 · 主要发明人:蒋捷、周天健(第2发明人)、李易珊 等

CN119540575B
Granted授权公告日 2025-04-08
Assignee专利权人 NUDT国防科技大学

Multi-scale semantic information enhancement method and apparatus for improving the performance of contrastive learning models 提升对比学习模型性能的多尺度语义信息增强方法和装置

National invention patent · inventors Jie Jiang, Tianjian Zhou (2nd inventor), Yishan Li, et al. 国家发明专利 · 主要发明人:蒋捷、周天健(第2发明人)、李易珊 等

CN119580024B
Granted授权公告日 2025-04-15
Assignee专利权人 NUDT国防科技大学

Pedestrian trajectory prediction method, apparatus and device 一种行人轨迹预测方法、装置及设备

National invention patent 国家发明专利

CN118364959B
Granted授权公告日 2025-04-01
Assignee专利权人 NUDT国防科技大学

Retinal image segmentation method and apparatus 一种视网膜图像分割方法及装置

National invention patent 国家发明专利

CN112001923B
Granted授权公告日 2021-01-05
Assignee专利权人 NUDT国防科技大学