Hyperbolic Representation Learning

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HiHR: Hierarchical Hyperbolic Representation for Aerial-Ground Person Re-Identification
Jul 10, 2026Qiwei Yang, Pingping ZhangHierarchical Representation Learning Hyperbolic Representation Learning
Dalian University of Technology, Dalian, China
Navigating Hierarchy: Hyperbolic Learning on Brain Graphs for Disorder Diagnosis
Jul 8, 2026Yapeng Li, Bo Jiang, Ziyan Zhang +2Medical Diagnosis Hierarchical Representation Learning
School of Computer Science and Technology, Anhui University, 111 Jiulong Road, Hefei, 230601, China
Is the Geometry Doing the Work? An Operating-Point Audit of Hierarchy in Hyperbolic Vision-Language Models
Jul 6, 2026Jaeyoung Kim, Eunseok Kim, Dongsuk JangVLM Evaluation Vision-Language Models
MADI
Group-Equivariant Poincaré Convolutional Networks
Jul 1, 2026Aiden Durrant, Rahul Baburajan, Georgios LeontidisEquivariant Neural Networks Hyperbolic Representation Learning
School of Computing Sciences, University of East Anglia, NR4 7TJ, Norwich, UK · Department of Physics and Technology, UiT The Arctic University of Norway, NO-9037, Tromsø, Norway
HyFL-CLIP: Hyperbolic Fine-Tuning of CLIP for Robust Long-Context Understanding
Jul 1, 2026Ji Ha Jang, Hayeon Kim, Chulwon Lee +2VLM Robustness Vision-Language Models
1Dept. of Electrical and Computer Engineering, 2IPAI, 3INMC & AIIS, Seoul National University, Republic of Korea
HyperVLP: Enhancing Hierarchical Surgical Video-Language Pre-training in Hyperbolic Space
Jun 30, 2026Yaojun Hu, Kun Yuan, Nassir Navab +3Hierarchical Representation Learning Surgical Video Understanding
Zhejiang University, Hangzhou, China · University of Strasbourg, CNRS, INSERM, ICube, UMR7357, Strasbourg, France · IHU Strasbourg, Strasbourg, France +1
Rank-Aware Hyperbolic Alignment for Vision-Language Dataset Distillation
Jun 28, 2026Jongoh Jeong, Sun-Kyung Lee, Kuk-Jin YoonDataset Distillation Vision-Language Alignment
Korea Advanced Institute of Science and Technology (KAIST), Republic of Korea · Electronics and Telecommunications Research Institute (ETRI), Republic of Korea
Two-dimensional Hyperbolic RNN Neural Quantum State
Jun 24, 2026H. L. DaoNeural Quantum States Recurrent Neural Networks
Hyperbolic Manifold Constrained Tabular Neural Network
Jun 23, 2026Tian Li, Huizhi Liang, Lucy Robinson +1Tabular Classification Tabular Representation Learning
Newcastle University Newcastle upon Tyne, UK
HypOProto: Hyperbolic Ordinal Prototypes for Left Ventricular Filling Pressure Classification
Jun 18, 2026Victoria Wu, Nima Hashemi, Hooman Vaseli +3Prototype-Based Classification Echocardiography
Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, BC, Canada · Vancouver General Hospital, Vancouver, BC, Canada
HyperVis: Continuous Latent Visual Relational Graphs on the Lorentz Hyperboloid for Compositional Reasoning
Jun 4, 2026Moshiur Farazi, Sameera Ramasinghe, Mahbub Ahmed Turza +1Visual Reasoning VLM Reasoning
Data Science and AI, University of Doha for Science and Technology, Qatar · Pluralis Research, Australia · Department of Electrical and Computer Engineering, North South University, Bangladesh
SkelHCC: A Hyperbolic CLIP-Driven Cache Adaptation Framework for Skeleton-based One-Shot Action Recognition
Jun 2, 2026Yanan Liu, Anqi Zhu, Jingmin Zhu +6Skeleton-Based Action Recognition Cross-Modal Representation Learning
Yunnan University, Kunming, China · Monash University · Lancaster University +1
SAHG: Sector-Anisotropic Hyperbolic Graph Model for Social Bot Detection
May 28, 2026Hanning Lu, Yingguang Yang, Jinwei Su +8Social Media Analysis Graph Neural Networks
University of Leeds · University of Science and Technology of China · 3South China Normal University +6
Temporal Hyperbolic Graph Representation Learning for Scale-Free Internet Routing and Delay Prediction
May 27, 2026Yi-Ling Kuo, Hao-Yu Tien, Shih-Yu TsaiTemporal GNNs Temporal Link Prediction
Department of Information Management and Finance, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan
H2G: Hierarchy-Aware Hyperbolic Grouping for 3D Scenes
May 12, 2026ByungHa Ko, Youngmin Lee, Dong Hwan KimClustering Hierarchical Representation Learning
Department of Computer Science and Engineering, Korea University · Intelligence and Interaction Research Center, Korea Institute of Science and Technology
HYPERPOSE: Hyperbolic Kinematic Phase-Space Attention for 3D Human Pose Estimation
May 11, 2026Vinduja Thekkath, Ashish Musale, Ajay Waghumbare +13D Human Pose Estimation Attention Mechanisms
HyNeuralMap: Hyperbolic Mapping of Visual Semantics to Neural Hierarchies
May 10, 2026Zihan Ma, Tian Xia, Kexin Wang +3Neural Representation Geometry Cross-Modal Alignment
School of Electronic Information (School of Artificial Intelligence), the Xi’an Key Laboratory of Radiomics and Intelligent Perception, Northwest University, Xi’an 710127, China
Semantic Alignment in Hyperbolic Space for Open-Vocabulary Semantic Segmentation
May 9, 2026Hoang M. Truong, Hai Nguyen-Truong, Dang HuynhVLM Adaptation Hierarchical Representation Learning
Fulbright University Vietnam
Curvature-Aware Captioning:Leveraging Geodesic Attention for 3D Scene Understanding
May 9, 2026Ziyao He, Yingjie Liu, ZhangYangRui +3Attention Mechanisms Hyperbolic Representation Learning
East China Normal University
Hyperbolic Concept Bottleneck Models
May 7, 2026Daniel Uyterlinde, Swasti Shreya Mishra, Pascal MettesConcept Bottleneck Models Hierarchical Representation Learning
Informatics Institute, University of Amsterdam, The Netherlands
Geometry-Aware State Space Model: A New Paradigm for Whole-Slide Image Representation
May 6, 2026Enhui Chai, Sicheng Chen, Tianyi Zhang +4Histopathology Image Classification Multiple Instance Learning
PuzzleLogic Pte Ltd, Singapore 229594, Singapore · Nhu Department of Electrical Engineering and Computer Science, University of California, Irvine · Department of Electrical & Computer Engineering, National University of Singapore
Hyp2Former: Hierarchy-Aware Hyperbolic Embeddings for Open-Set Panoptic Segmentation
May 4, 2026Yao Lu, Rohit Mohan, Florian Drews +2Image Segmentation Panoptic Segmentation
Department of Computer Science, University of Freiburg, Germany · Bosch Research, Robert Bosch GmbH, Germany
A Unified Framework of Hyperbolic Graph Representation Learning Methods
Apr 30, 2026Sofía Pérez Casulo, Marcelo Fiori, Bernardo Marenco +1Graph Representation Learning Graph Embedding
Facultad de Ingenier´ıa, Universidad de la Rep´ublica, Uruguay · Centro Interdisciplinario en Ciencia de Datos y Aprendizaje Autom´atico (CICADA), Universidad de la Rep´ublica, Uruguay
HAC: Parameter-Efficient Hyperbolic Adaptation of CLIP for Zero-Shot VQA
Apr 26, 2026Francesco Dibitonto, Cigdem Beyan, Vittorio MurinoVisual Question Answering Zero-Shot Learning
Department of Computer Science, University of Verona, Verona, Italy · EVS - Embedded Vision Systems Srl, Verona, Italy · AI for Good (AIGO), Istituto Italiano di Tecnologia, Genova, Italy
HypEHR: Hyperbolic Modeling of Electronic Health Records for Efficient Question Answering
Apr 22, 2026Yuyu Liu, Sarang Rajendra Patil, Mengjia Xu +1Healthcare Hierarchical Representation Learning
Department of Computer Science, Stony Brook University · Department of Data Science, New Jersey Institute of Technology · Department of Biomedical Informatics, Stony Brook University
HSG: Hyperbolic Scene Graph
Apr 19, 2026Liyang Wang, Zeyu Zhang, Hao TangGraph Representation Learning Hierarchical Representation Learning
School of Computer Science, Peking University
Modeling Multi-Dimensional Cognitive States in Large Language Models under Cognitive Crowding
Apr 19, 2026Lin Zhong, Siyu Zhu, Zizhen Yuan +5LLM Alignment Cognitive Modeling
Harbin Institute of Technology, Shenzhen, China · City University of Macau, Macao SAR, China · Peng Cheng Laboratory, Shenzhen, China
Hyperbolic Enhanced Representation Learning for Incomplete Multi-view Clustering
Apr 18, 2026Tianyi Chen, Haobo Wang, Kai Tang +5Contrastive Learning Hierarchical Representation Learning
School of Software Technology, Zhejiang University, Zhejiang 310027, China · College of Computer Science and Technology, Zhejiang University, Zhejiang 310027, China · Beijing Key Laboratory of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing 100044, China +2
Lorentz Framework for Semantic Segmentation
Apr 18, 2026Zahid Hasan, Masud Ahmed, Nirmalya RoySegmentation Uncertainty Estimation Semantic Segmentation
Department of Information Systems, University of Maryland, Baltimore County
Uncertainty-guided Compositional Alignment with Part-to-Whole Semantic Representativeness in Hyperbolic Vision-Language Models
Mar 23, 2026Hayeon Kim, Ji Ha Jang, Junghun James Kim +1Vision-Language Models Hierarchical Representation Learning
Dept. of Electrical and Computer Engineering, Seoul National University, Republic of Korea · INMC & IPAI, Seoul National University, Republic of Korea

Jul 10, 2026, cs.CVJ/K move · Enter open · S save

HiHR: Hierarchical Hyperbolic Representation for Aerial-Ground Person Re-Identification

Qiwei Yang, Pingping Zhang

Dalian University of Technology, Dalian, China

Hierarchical Representation Learning Hyperbolic Representation Learning Person Re-Identification

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Aerial-Ground Person Re-IDentification (AG-ReID) aims to retrieve the same person across heterogeneous aerial and ground camera platforms. Although great progress has been made, existing methods remain suboptimal due to the direct feature alignment across views, overlooking view-specific cues. To address this issue, we propose a novel Hierarchical Hyperbolic Representation (HiHR) framework for AG-ReID. More specifically, we first extract multi-granularity features based on pre-trained visual-text encoders. Then, we propose a Text-guided Multi-granularity Fusion (TMF) to fuse multi-granularity features and enhance the representation ability of identity features. Furthermore, we introduce the Hierarchical Hyperbolic Learning (HHL) to construct a hierarchical feature structure in a hyperbolic space. This hierarchy includes a coarse level that ensures identity separability and cross-view consistency, and a fine level that preserves view-specific discriminative cues. As a result, our proposed framework can effectively aggregate view-invariant and view-specific discriminative features for AG-ReID. Extensive experiments on four AG-ReID benchmarks demonstrate the effectiveness of our framework. The source code is available at https://github.com/YangQiWei3/HiHR.

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