Vision Foundation Model Adaptation

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22 papers in the last four weeks, up 83% on the four weeks before. 0.2% of all new papers.

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IJCB-AFMFR 2026: Competition on Adapting Foundation Models for Face Recognition Using Synthetic Training Data
Jul 27, 2026Tahar Chettaoui, Guray Ozgur, Eduarda Caldeira +13VLM Adaptation Vision Foundation Model Adaptation
Fraunhofer Institute for Computer Graphics Research IGD, Germany · Technical University of Darmstadt, Germany · Vilnius University, Lithuania +5
Parameter-Efficient Adaptation of SAM3 for Prompt-Driven Surgical Concept Segmentation
Jul 26, 2026Changjing Liu, Yiming Huang, Beilei Cui +5Promptable Image Segmentation Vision Foundation Model Adaptation
Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China · XGEN Labs
Rethinking Layer-Wise Information Allocation for Vision Foundation Model Adaptation
Jul 24, 2026Yuqi Li, Xi Xiao, Yunbei Zhang +6Information Bottleneck Vision Foundation Model Adaptation
City College of New York, CUNY · New York, NY, USA · University of Alabama at Birmingham +11
DINO-VPT: Hierarchical Visual Prompt Tuning for Joint Physical-Digital Face Anti-Spoofing
Jul 23, 2026Pierre Gallin-Martel, Mika Feng, Koichi Ito +1Vision Foundation Model Adaptation Face Presentation Attack Detection
Graduate School of Information Sciences, Tohoku University, Japan
Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data
Jul 20, 2026Samy Mounir, Mikolaj Cieslak, Najmeddine Dhieb +8Synthetic-to-Real Domain Adaptation Plant Phenotyping
Computer, Electrical and Mathematical Sciences and Engineering Division, KAUST, KSA · Department of Computer Science, University of Calgary, Canada · Department of Computer Science, Kiel University, Germany +2
DepthART: Scaling Foundation Monocular Depth to Tiny Models
Jul 19, 2026Feng Xue, Wu Chen, Mingshuai Zhao +7Metric Depth Estimation Monocular Depth Estimation
University of Trento Trento, Italy · Beijing University of Posts and Telecommunications Beijing, China · The Hong Kong University of Science and Technology Hong Kong, China +1
Parameter-efficient Prompt Tuning of Vision Foundation Model With Adaptive Focal Loss for Interpretable MCI Screening
Jul 16, 2026Javad Khoramdel, Farhad Hoseyni, Amirhossein NikoofardClass-Imbalanced Learning Vision Foundation Model Adaptation
APAC Research Group, Faculty of Electrical Engineering, K. N. Toosi University of Technology, Tehran, Iran
XCT-SAM: Sequential Parameter-Efficient Domain Adaptation of SAM for Industrial XCT Defect Segmentation
Jul 15, 2026Md Mahedi Hasan, Md Mushfiqur Rahaman, Alan Pachkovskiy +3Domain Adaptation Vision Foundation Model Adaptation
Lane Department of Computer Science & Electrical Engineering West Virginia University, Morgantown, WV · Department of Industrial and Management Engineering West Virginia University, Morgantown, WV · School of Mathematical and Data Sciences West Virginia University, Morgantown, WV
Scalable and Trustworthy Earth Observation Foundation Models
Jul 8, 2026Syed Usama Imtiaz, Mitra Nasr Azadani, Nasrin AlamdariGeospatial Foundation Models Vision Foundation Model Adaptation
Department of Civil and Environmental Engineering, Florida State University
LoCA: Spatially-Aware Low-Rank Convolutional Adaptation of Vision Foundation Models
Jul 8, 2026Sojung An, Junha Lee, Sujeong You +2Vision Foundation Model Adaptation Low-Rank Adaptation
Korea University, Seoul, Republic of Korea · Korea Institute of Industrial Technology, Ansan, Republic of Korea · Seoul National University, Seoul, Republic of Korea
Token-Based Dual-view Fusion and Adaptation of Large Vision Models for Breast Cancer Classification
Jul 7, 2026Aysan Ghayouri Pirsoltan, Shima Babakordi, Mohammad Reza MohammadiCross-Attention Multi-View Learning
School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran · School of Computer Engineering, Iran University of Science and technology, Tehran, Iran
A Step Towards Robust Unsupervised Domain Adaptation via Fine-Tuning and Reinforcement Learning
Jul 3, 2026Sushant Dagaji Desale, Rahul Mishra, Ashutosh Kumar SinhaAdversarial Training Unsupervised Domain Adaptation
Indian Institute of Technology Patna
RayTun3R: Online Camera Adaptation in 3D Foundation Models
Jul 2, 2026Daniil Sinitsyn, Nikita Araslanov, Daniel Cremers3D Foundation Models Test-Time Adaptation
1TU Munich · 2Munich Center for Machine Learning · University of Oxford
When Does Resolution Help a Frozen Backbone? Global Attention at Resolution Predicts Scalable Adaptation for Camouflaged and Marine Animal Segmentation
Jul 2, 2026Tyler Rust, Chandra KambhamettuImage Segmentation Vision Foundation Model Adaptation
University of Delaware · University of South Florida
Efficient PEFT Methods with Adaptive Checkpointing for Vision Models and VLMs on Resource Constrained Consumer-GPUs
Jul 2, 2026Altay Toktassyn, Jurn-Gyu ParkFine-Tuning Memory-Efficient Fine-Tuning
Department of Computer Science, Nazarbayev University, Astana 010000, Kazakhstan
AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting
Jul 2, 2026Muhammad Ibraheem Siddiqui, Muhammad Haris KhanTest-Time Adaptation Vision Foundation Model Adaptation
Mohamed Bin Zayed University of Artificial Intelligence
LiZAD: A Lightweight Zero-Shot Anomaly Detection Framework for Industrial Manufacturing
Jul 2, 2026Uzair Khan, Luigi Capogrosso, Muhammad Aqeel +3Edge Inference Industrial Anomaly Detection
University of Verona · Interdisciplinary Transformation University of Austria · ETH Zurich
Hidden-Shot: Towards One-Shot Task Generalization for Low-Level Vision Generalist Models
Jul 1, 2026Shao-Jun Xia, Xianzheng Ma, Zichong MengVision Foundation Model Adaptation Few-Shot Learning
Pratt School of Engineering, Duke University, Durham, NC, 27708, USA · Department of Engineering Science, University of Oxford, Oxford, Parks Road, OX1 3PJ, UK · Khoury College of Computer Science, Northeastern University, Boston, MA, 02115, USA
RetailSMV: Exocentric vs. Egocentric Adaptation of Foundation Video World Models in Retail
Jul 1, 2026Amirreza Rouhi, Rajat Aggarwal, Parikshit Sakurikar +2Vision Foundation Model Adaptation Video Prediction
DreamVu
FaceMoE: Mixture of Experts for Low-Resolution Face Recognition
Jun 30, 2026Kartik Narayan, Vishal M. PatelVision Foundation Model Adaptation Face Recognition
Johns Hopkins University
Uncertainty-Aware Last-Layer Adaptation of RETFound for Referable Diabetic Retinopathy Screening Under Dataset Shift
Jun 30, 2026Karim MardhaniBayesian Neural Networks Distribution Shift Robustness
University of Colorado Boulder Boulder, CO, USA
Semantic-Driven Scale and Spatial Selection for Efficient Cross-Modal Alignment in Referring Remote Sensing Image Segmentation
Jun 29, 2026Kun Li, Shengxi Gui, Francesco Nex +1Remote Sensing Image Segmentation Cross-Modal Alignment
University of Liverpool, UK · University of Michigan, USA · University of Twente, NL +1
How many labels do you need? A decision framework for cross-habitat marine species recognition
Jun 28, 2026Alzayat Saleh, Mostafa Rahimi AzghadiDomain Generalization Vision Foundation Model Adaptation
College of Science and Engineering, James Cook University, Townsville, QLD, Australia · Centre for AI and Data Science Innovation, James Cook University, Townsville, QLD, Australia
TextDS: Parameter-Efficient Representation Alignment for Scene Text Detection under Distribution Shifts
Jun 26, 2026Boyuan Chen, Zichen Dang, Chuang Yang +2Distribution Shift Robustness Domain Generalization
School of Electrical Engineering, Xi’an Jiaotong University · Department of Electrical and Electronic Engineering, The Hong Kong Polytechnic University
Layer-Specific Prompt Fusion Discovery via Differentiable Search in Vision Foundation Models
Jun 24, 2026Xi Xiao, Xingjian Li, Yunbei Zhang +7Vision Transformer Vision Foundation Model Adaptation
UAB · CMU · Tulane +3
REDI-Match: Rotation-Equivariant Distillation for Efficient and Robust Dense Matching
Jun 23, 2026Yinji Ge, Guixu Zheng, Wulong Guo +5Vision Foundation Model Adaptation Geometric Representation Learning
1Tsinghua University · 2Southern University of Science and Technology · 3Beihang University +1
MorVess: Morphology-Aware Pulmonary Vessel Segmentation Network
Jun 23, 2026Fuyou Mao, Yifei Chen, Beining Wu +9Vision Foundation Model Adaptation Topology-Preserving Image Segmentation
Central South University, 410083 Changsha, China · Tsinghua University, 100084 Beijing, China · Hangzhou Dianzi University, 310018 Hangzhou, China +1
Flood Mapping from RGB imagery using a Vision Foundation Model
Jun 23, 2026Vladyslav Polushko, Tilman Bucher, Ronald Rösch +3Remote Sensing Image Segmentation Geospatial Foundation Models
Image Processing Department, Fraunhofer ITWM, Kaiserslautern, Germany · Institut für Optische Sensorsysteme, DLR, Berlin, Germany · ACIDA Lab, Hochschule Darmstadt, Darmstadt, Germany +1
Technical Report for the ICRA 2026 GOOSE 2D Fine-Grained Semantic Segmentation Challenge: Pretraining-Diverse Ensemble of Foundation Vision Encoders for Robust Outdoor Scene Understanding
Jun 22, 2026Boyan Wang, Yongxi Huang, Wenjing Li +4Vision Foundation Model Adaptation Deep Ensembles
LION Lab, Hefei University of Technology, Hefei, China. · University of Macau, Macau, China.
Concept Alignment Contrast and Long-Short Prompt Memory for Test-Time Adaptation of SAM3 in Medical Image Segmentation
Jun 22, 2026Yubo Zhou, Jianghao Wu, Ping Ye +2Test-Time Adaptation Promptable Image Segmentation
University of Electronic Science and Technology of China, Chengdu, China · Faculty of Information Technology, Monash University, Melbourne, VIC 3800, Australia · Shanghai Artificial Intelligence Laboratory, Shanghai, China

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IJCB-AFMFR 2026: Competition on Adapting Foundation Models for Face Recognition Using Synthetic Training Data

Tahar Chettaoui, Guray Ozgur, Eduarda Caldeira, Arturas Nakvosas+12

Fraunhofer Institute for Computer Graphics Research IGD, Germany · Technical University of Darmstadt, Germany · Vilnius University, Lithuania+5

VLM Adaptation Vision Foundation Model Adaptation Face Recognition

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This paper presents a summary of the Competition on Adapting Foundation Models for Face Recognition Using Synthetic Training Data (AFMFR), held at the 2026 International Joint Conference on Biometrics (IJCB 2026). The competition received a total of eight valid submissions from four distinct teams across two complementary tracks: a Full Data Track, in which participants adapt the CLIP ViT-L/14 foundation model using large-scale synthetic identity data, and a Limited Data Track, designed to reflect more resource-constrained adaptation regimes. All training data was generated exclusively using IDPERTURB. Submitted solutions are ranked based on verification and identification performance across a diverse suite of benchmarks, including LFW, CFP-FP, AgeDB-30, CALFW, CPLFW, IJB-B, IJB-C, and TinyFace, using the Borda count method. Fairness evaluation is additionally conducted on the RFW dataset across four demographic groups. The results demonstrate that adaptation of the CLIP foundation model with synthetic training data substantially improves over the off-the-shelf model and, in several cases, surpasses the baseline. Notably, full fine-tuning with Sub-Center ArcFace (DMSTI-Neurotechnology) leads the Full Data Track, while rank-stabilized LoRA adaptation (Idiap-BSP) proves most effective under limited-data conditions.

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