Cross-Modal Feature Matching

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7 papers in the last four weeks, against 2 the four weeks before. 0.1% of all new papers.

Jul 13Week of Sep 28

Latest papers 41

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ARCH-B: Architectural Representation, Comprehension and Hierarchy Benchmark
Sep 28, 2026Kieran Sagar Parikh, Jose Luis Garcia del Castillo y LopezSemantic Correspondence Cross-Modal Alignment
Harvard University · Northeastern University
MatcherCompass: A Deployment-Aware Benchmark to Guide Image Matcher Selection in the Wild
Sep 22, 2026Hyunwoo Kim, Giseop KimImage Matching Cross-Modal Feature Matching
Department of Robotics and Mechatronics Engineering, DGIST, Daegu, Republic of Korea
Mask 2D-3D: Adaptive Dual-Masked Autoencoder Network for Image-to-Point Cloud Registration
Sep 16, 2026Zhixin Cheng, Jiacheng Deng, Xiaotian Yin +3Masked Autoencoders Point Cloud Registration
School of Computer Science and Technology, Hefei University of Technology, Hefei 230601, China · School of Information Science and Technology, University of Science and Technology of China, Hefei 230027, China · Institute of Advanced Technology, University of Science and Technology of China, Hefei 230027, China
Beyond Ambiguous Visual Cues: Studying Physiological Disruptions and Cross-Modal Inconsistencies in Deepfake Videos
Sep 14, 2026Chenxi Yang, Yassine Ouzar, Larbi BoubchirRemote Photoplethysmography Deepfake Detection
LIASD Laboratory Shanghai Jiaotong University Shanghai, China · LIASD Laboratory University of Paris 8 Saint-Denis, France
Multimodal Floorplan Encoding: Learning Dense Modality-Invariant Representations
Sep 14, 2026Xavier Anadón, Rémi Pautrat, Rui WangRepresentation Learning Cross-Modal Representation Learning
University of Zaragoza, Spain · Microsoft, Switzerland
RoMa- $Ω$ : What Feed-Forward 3D Models Know About Image Matching
Sep 8, 2026David Nordström, Xinyue Zhang, Thibaut Loiseau +2Image Matching 3D Representation Learning
Chalmers University of Technology, Sweden · Mobile Perception Lab, ShanghaiTech University, China · LIGM, Ecole des Ponts, Univ. Gustave Eiffel, CNRS, France
DXPR: Depth-Based Vision-LiDAR Cross-Modal Place Recognition Using Vision Foundation Models
Sep 8, 2026Yungsoo Han, Youngseok Jang, Seungwon Roh +2LiDAR Place Recognition Visual Place Recognition
Department of Aerospace Engineering, Seoul National University, Seoul, Republic of Korea. · InnoCORE AI-Transformed Aerospace Research Center, KAIST, Daejeon, Republic of Korea. · Interdisciplinary Program in Artificial Intelligence, Seoul National University, Seoul, Republic of Korea.
CrossFeat: Bridging Imaging Modalities in Feature Descriptor Space
Aug 31, 2026Paul Schneider, Nazim HaouchineCross-Modal Representation Learning Multimodal Disentangled Representation Learning
Harvard Medical School, Brigham and Women’s Hospital, Boston, MA, USA · Technical University of Munich, Munich, Germany
TeaMatch: Teachable Cross-Modal Representation Learning for 2D-3D Matching
Aug 10, 2026Chongjian Wang, Junjie GaoCross-Modal Representation Learning Image Matching
Shandong Women’s University · Jinan, China · Shandong University of Science and Technology +1
SLAP: Selective Local Vision-Language Alignment for Fish Re-Identification via Partial Optimal Transport
Aug 9, 2026Cigdem Beyan, Tonje Knutsen Sordalen, Kim Tallaksen HalvorsenInverse Optimal Transport Animal Re-Identification
Department of Computer Science, University of Verona, 37134 Verona, Italy · Institute of Marine Research, Nye Flødevigveien 20, 4817 His, Norway · University of Agder, Centre for Coastal Research, 4604 Grimstad, Norway
Face and Voice Cross-modal Association with Learning Convex Feature Embedding
Jul 30, 2026Taewan Kim, Jiwoo KangCross-Modal Feature Matching
1Data Science Major, Dongduk Women’s University, Seoul, 02748, South Korea. · 2*Division of Artificial Intelligence Engineering, Sookmyung Women’s University, Seoul, 04310, South Korea.
XMatchAD: A Cross-Modal Matching Perspective on Reconstruction-based Anomaly Detection
Jul 26, 2026Mingxiu Cai, Zhe Zhang, Gaochang Wu +1Industrial Anomaly Detection Anomaly Localization
State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China
Cross-Coordinate Correspondence Pruning for Image-to-Point Cloud Registration
Jul 19, 2026Xin Liu, Rong Qin, Huipeng Lin +5Point Cloud Registration Cross-Modal Feature Matching
VCIP & TMCC & DISSec, College of Computer Science, Nankai University, Tianjin, China. · AutoCity (Shenzhen) Autonomous Driving Co., Ltd, Shenzhen, China. · School of Intelligent Science and Technology, University of Science and Technology Beijing, Beijing, China. +4
SUFLECA: Scaling Up Feature Learning for CAD-to-image Alignment
Jul 16, 2026Saad Ejaz, Miguel Fernandez-Cortizas, Javier Civera +2Object Pose Estimation Geometric Representation Learning
Automation and Robotics Research Group, Interdisciplinary Centre for Security, Reliability, and Trust (SnT), University of Luxembourg, Luxembourg · I3A, Universidad de Zaragoza
Label-Free Target-Domain Adaptation for Unconstrained Event-Image Feature Matching via Dual-Stage Distillation
Jul 11, 2026Zhonghua Yi, Hao Shi, Qi Jiang +3Event-Based Vision Cross-Modal Knowledge Distillation
Zhejiang University · Ant Group · National University of Defense Technology +1
PLGSA-Transformer: Periocular Landmark-Guided Attention with Occlusion-Adaptive Cosine Thresholding for Cross-Modal Masked and Unmasked Face Recognition
Jul 3, 2026Dana A AbdullahCross-Modal Feature Matching Face Recognition
Faculty of Engineering and Computer Science, Qaiwan International University, Sulaymaniyah, KRG, Iraq. · Department of Information and Communication Technology Center (ICTC)-System Information, Ministry of Higher Education and Scientific Research.
DetailAnywhere: Fashion Detail Generation via Cross-Modal Feature Alignment Distillation
Jul 2, 2026Zijun Li, Yimin Zhou, Jia Sun +12Diffusion Model Distillation Conditional Image Generation
1Kuaishou Technology · 2AIM for Health Lab, Monash University
Cross4D-JEPA: Dense Cross-modal Correspondence Distillation for 4D Point Cloud Representation Learning
Jul 1, 2026Trung Thanh Nguyen, Hai Nguyen-Truong, Tu Vo +2Cross-Modal Knowledge Distillation Point Cloud Learning
Nagoya University, Japan · Northeastern University, USA · KC Machine Learning Lab, Korea +2
AnyMatch: Supercharging Universal Multi-Modal Image Matching with Large-Scale Single-View Images
Jun 30, 2026Meng Yang, Zizhuo Li, Linfeng Tang +2Synthetic Data Augmentation Cross-Modal Feature Matching
Electronic Information School1, Wuhan University, Wuhan 430072, China · School of Robotics, Wuhan University2, Wuhan 430072, China
Clinical Risk-Aware Multi-Level Grading for Coronary Artery Stenosis through Curved Feature Reconstruction
Jun 29, 2026Shishuang Zhao, Hongtai Li, Junjie Hou +13D Medical Imaging Cross-Modal Feature Matching
Yizhun Medical AI Co., Ltd · The First Hospital of China Medical University
Cross-Spectral Stereo Inertial Odometry
Jun 29, 2026Seungsang Yun, Hyunsoo Jang, Tai Hyoung Rhee +3Visual-Inertial Odometry Cross-Modal Feature Matching
Dept. of Mechanical Engineering, Seoul National University (SNU), Seoul, S. Korea
CMDS-AD: Cross-Modal Dual-Stream Decoupling for Few-Shot Anomaly Detection
Jun 18, 2026Junhao Cai, Junyu Chen, Deyu Zeng +4Few-Shot Anomaly Detection Multimodal Anomaly Detection
Shenzhen University, Shenzhen, Guangdong 518060, China · Guangzhou Maritime University, Guangzhou, Guangdong 510725, China · Hong Kong University of Science and Technology (Guangzhou), Guangzhou, Guangdong 511453, China
G2IA: Geometry-Guided Instance-Aware Retrieval and Refinement for Cross-Modal Place Recognition
Jun 13, 2026Xianyun Jiao, Jingyi Xu, Zhongmiao Yan +2LiDAR Place Recognition Visual Place Recognition
Shanghai Jiao Tong University · National University of Defense Technology
FIGMA: Towards FIne-Grained Music retrievAl
Jun 4, 2026Nishit Anand, Ashish Seth, Sreyan Ghosh +2Audio Understanding Audio-Text Retrieval
University of Maryland, College Park, USA
Geometry-Preserving Unsupervised Alignment for Heterogeneous Foundation Models
Jun 3, 2026Shuwen Yu, Zhanxuan Hu, Yi Zhao +2Cross-Modal Representation Learning Vision Foundation Model Adaptation
Yunnan Normal University, Kunming, China · Kunming University of Science and Technology, Kunming, China
Cross-Modality Feature Fusion Based on Structured State Space Duality for Multimodal Image Registration Network
Jun 2, 2026Zhikang Li, Yan Wu, Xin Hu +2Multi-Scale Feature Fusion Cross-Modal Feature Matching
Remote Sensing Image Processing and Fusion Group, School of Electronic Engineering, Xidian University, Xi’an 710071, China · National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China
Best Segmentation Buddies for Image-Shape Correspondence
May 18, 2026Itai Lang, Dongwei Lyu, Dale Decatur +13D Semantic Segmentation Cross-Modal Feature Matching
University of Chicago
Mind the Gap: Learning Modality-Agnostic Representations with a Cross-Modality UNet
May 16, 2026Xin Niu, Enyi Li, Jinchao Liu +3Cross-Modal Learning Cross-Modal Representation Learning
Tianjin Key Laboratory of Intelligent Robotics, College of Artificial Intelligence, Nankai University, China, and also with Engineering Research Center of Trusted Behavior Intelligence, Ministry of Education, Nankai University, China. · VisionMetric Ltd, Canterbury, Kent, UK. · Department of Computer Science, Haifa University, Israel.
Learning Relative Representations for Fine-Grained Multimodal Alignment with Limited Data
May 16, 2026Shiwon Kim, Yu Rang ParkCross-Modal Learning Representation Learning
Yonsei University
VoxCor: Training-Free Volumetric Features for Multimodal Voxel Correspondence
May 13, 2026Guney Tombak, Ertunc Erdil, Ender KonukogluMedical Imaging Foundation Models Cross-Modal Representation Learning
Biomedical Image Computing Group, ETH Zurich, Zurich, Switzerland · The LOOP Zurich – Medical Research Center, Zurich, Switzerland

Sep 28, 2026, cs.CVJ/K move · Enter open · S save

ARCH-B: Architectural Representation, Comprehension and Hierarchy Benchmark

Kieran Sagar Parikh, Jose Luis Garcia del Castillo y Lopez

Harvard University · Northeastern University

Semantic Correspondence Cross-Modal Alignment Cross-Modal Feature Matching Multimodal Model Evaluation

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Multimodal models increasingly interpret visual environments, but their ability to recognize the same building across photographs, floor plans, elevations, sections, and renderings remains poorly characterized. We introduce ARCH-B, a benchmark of 354 four-choice questions across 11 cross-representational archetypes, constructed from a building-linked corpus of 3.9 million architectural images using visually similar distractors, model-guided difficulty screening, and manual validation. We evaluate 25 multimodal models and collect 5,830 responses from non-expert human participants. Model accuracy ranges from 10.45% to 83.90%, compared with a human baseline of 35.35%. Models perform comparatively well on mixed-representation outlier detection and photograph matching, but remain weaker on floorplan-to-photograph correspondence. Human and model difficulty across archetypes is only weakly correlated (Spearman's (ρ=0.33)). Held-out evaluation confirms that the difficulty identified during screening generalizes beyond the curation models. ARCH-B provides a diagnostic evaluation of visual correspondence and representation transfer across architectural media.

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