The recent surge in 3D data acquisition has spurred the development of geometric deep learning models for point cloud processing, boosted by the remarkable success of transformers in natural language processing. While point cloud transformers (PTs) have achieved impressive results recently, their quadratic scaling with respect to the point cloud size poses a significant scalability challenge for real-world applications. To address this issue, we propose the Adaptive Point Cloud Transformer (AdaPT), a standard PT model augmented by an adaptive token selection mechanism. AdaPT dynamically reduces the number of tokens during inference, enabling efficient processing of large point clouds. Furthermore, we introduce a budget mechanism to flexibly adjust the computational cost of the model at inference time without the need for retraining or fine-tuning separate models. Our extensive experimental evaluation on point cloud classification tasks demonstrates that AdaPT significantly reduces computational complexity while maintaining competitive accuracy compared to standard PTs. The code for AdaPT is made publicly available.
DAPoinTr: Domain Adaptive Point Transformer for Point Cloud Completion
Deakin University（迪肯大学）；Shanghai Jiao Tong University（上海交通大学）；East China Normal University（华东师范大学）；Zhejiang University（浙江大学）；The University of Western Australia（西澳大学）
Adaptive Multi-view and Temporal Fusing Transformer for 3D Human Pose Estimation
Nanjing University of Information Science and Technology（南京信息工程大学）
本文提出了一种统一的框架称为多视图和时间融合Transformer（MTF-Transformer），以适应不同的视图数和视频长度，而无需摄像机校准的三维人体姿态估计（HPE）。它由特征提取器、多视图融合Transformer（MFT）和时间融合Transformer（TFT）组成。特征提取器从每个图像中估计2D姿态，并根据置信度融合预测。它提供了以姿势为中心的特征嵌入，并使后续模块在计算上轻量化。MFT融合了不同数量的视图与一个新的相对注意力块的功能。它自适应地测量每对视图之间的隐式相对关系，并重建更多的信息特征。TFT聚合整个序列的特征并通过Transformer预测3D姿态。它自适应地处理任意长度的视频，并充分利用时间信息。Transformers的迁移使我们的模型能够更好地学习空间几何，并为不同的应用场景保持鲁棒性。我们报告了Human3.6M、TotalCapture和KTH Multiview Football II的定量和定性结果。与相机参数的最先进的方法相比，MTF变压器获得了有竞争力的结果，并推广到动态捕捉与任意数量的不可见的意见。
Exploring Sequence Feature Alignment for Domain Adaptive Detection Transformers
University of Science and Technology of China（中国科学技术大学）；Institute of Artificial Intelligence, Hefei Comprehensive National Science Center（合肥综合性国家科学中心人工智能研究院）；The University of Sydney（悉尼大学）；JD Explore Academy（京东探索研究院）；Nanyang Technological University（南洋理工大学）
Adaptive Token Sampling For Efficient Vision Transformers
Technische Universität Berlin（柏林工业大学）；Berlin Institute for the Foundations of Learning and Data（柏林学习与数据基础研究所）；University of Bonn（波恩大学）；Microsoft（微软）；University of California, Davis（加州大学戴维斯分校）；Meta Reality Labs（Meta现实实验室）
Adaptive Routing for Efficient Diffusion Transformer-Based PNI Prediction
Seoul National University（首尔国立大学）；Kyung Hee University（庆熙大学）；OUTTA；Chung-Ang University（Chung-Ang 大学）；Seoul National University School of Medicine（首尔国立大学医学院）；Samsung Changwon Hospital（三星昌原医院）；Samsung Medical Center（三星医疗中心）；NVIDIA AI Technology Center（NVIDIA AI 技术中心）
Adaptive Transformer Attention and Multi-Scale Fusion for Spine 3D Segmentation
University of Houston（休斯顿大学）；New York University（纽约大学）；University of Massachusetts Boston（马萨诸塞大学波士顿分校）；University of North Carolina at Chapel Hill（北卡罗来纳大学教堂山分校）；Tulane University（杜兰大学）
End-to-End Object Detection with Adaptive Clustering Transformer
Peking University（北京大学）；Shanghai AI Laboratory（上海人工智能实验室）；CUHK-SenseTime Joint Laboratory（香港中文大学-商汤科技联合实验室）；The Chinese University of Hong Kong（香港中文大学）
ART: Adaptive Relational Transformer for Pedestrian Trajectory Prediction with Temporal-Aware Relations
Department of Computer Science, Durham University（杜伦大学计算机科学系）；School of Computing and Information Systems, Singapore Management University（新加坡管理大学计算与信息系统学院）
TAT-VPR: Ternary Adaptive Transformer for Dynamic and Efficient Visual Place Recognition
School of Electronics and Computer Science, University of Southampton（南安普顿大学电子与计算机科学学院）；School of Electrical Engineering and Computer Science, Queensland University of Technology（昆士兰理工大学电气工程与计算机科学学院）；School of Computer Science and Electronic Engineering, University of Essex（埃塞克斯大学计算机科学与电子工程学院）
DAMSDet: Dynamic Adaptive Multispectral Detection Transformer with Competitive Query Selection and Adaptive Feature Fusion
School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications（重庆邮电大学通信与信息工程学院）；School of Mathematics and Statistics, Xi’an Jiaotong University（西安交通大学数学与统计学院）；School of Intelligent Systems Engineering, Sun Yat-sen University（中山大学智能系统工程学院）
Transformer-Guided Content-Adaptive Graph Learning for Hyperspectral Unmixing
School of Automation Engineering, Shanghai University of Electric Power（上海电力大学自动化工程学院）；School of Mechatronic Engineering and Automation, Shanghai University（上海大学机电工程与自动化学院）；School of Intelligent Systems Engineering, Sun Yat-sen University（中山大学智能系统工程学院）
AdaptiveClick: Clicks-aware Transformer with Adaptive Focal Loss for Interactive Image Segmentation
College of Computer Science and Electronic Engineering, Hunan University（湖南大学计算机与电子工程学院）；Institute for Artificial Intelligence, the University of Stuttgart（斯图加特大学人工智能学院）
FreqDGT: Frequency-Adaptive Dynamic Graph Networks with Transformer for Cross-subject EEG Emotion Recognition
Department of Chinese and Bilingual Studies, The Hong Kong Polytechnic University（中文与双语研究系，香港理工大学）；School of Information Engineering, Shanghai Maritime University（信息工程学院，上海海洋大学）
SDiT: Semantic Region-Adaptive for Diffusion Transformers
University of Houston（德克萨斯大学奥斯汀分校）；Rice University（里奇大学）；Indiana University Bloomington（印第安纳大学布卢明顿分校）；Argonne National Laboratory（阿贡国家实验室）；National University of Singapore（新加坡国立大学）
Transcending the Limit of Local Window: Advanced Super-Resolution Transformer with Adaptive Token Dictionary
University of Electronic Science and Technology of China（电子科技大学）；Computer Vision Lab, ETH Zürich（苏黎世联邦理工学院计算机视觉实验室）；Integrated Systems Laboratory, ETH Zürich（苏黎世联邦理工学院集成系统实验室）
Enhancing Image Restoration Transformer via Adaptive Translation Equivariance
Institute of Medical Technology, Peking University Health Science Center, Peking University（北京大学医学部医学技术研究所）；Biomedical Engineering Department, College of Future Technology, Peking University（未来技术学院生物医学工程系）；National Biomedical Imaging Center, Peking University（北京大学国家生物医学成像中心）；China Mobile Research Institute（中国移动研究院）
Scene Adaptive Sparse Transformer for Event-based Object Detection
University of Science and Technology of China（中国科学技术大学）；Institute of Artificial Intelligence, Hefei Comprehensive National Science Center（合肥综合性国家科学中心人工智能研究院）
