3.6k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Inception Institute of Artificial IntelligenceAE16 papers
- Carnegie Mellon UniversityUS15 papers
- École PolytechniqueFR11 papers
- Australian National UniversityAU10 papers
- Nankai UniversityCN8 papers
- Centre de Mathématiques Appliquées de l'École polytechniqueFR7 papers
- Nanyang Technological UniversitySG7 papers
- National Research University Higher School of EconomicsRU7 papers
- The University of SydneyAU7 papers
- University of WaterlooCA7 papers
- Hamad bin Khalifa UniversityQA6 papers
- Moscow Institute of Physics and TechnologyRU6 papers
56 papers · 1 filter
PhaseAT: Fourier Phase Adversarial Training for Medical Image Domain Generalization
Ahmed Sharshar, Asif Hanif, Naveen Kumar Kummari +2
Reliable clinical deployment of deep medical image models is hindered by distribution shifts across scanners, sites, and acquisition protocols. Existing domain generalization (DG)…
Cross-Domain Generalization in Machine Unlearning via Label-Conditioned Energy Magnitude Regularization
Syed Ali Ahmed, Syed Bilal Ahsan, Muhammad Zaigham Zaheer
Machine unlearning removes the influence of specific data from a trained model. However, most methods treat the forgotten concept as isolated. In this paper, we study what happens…
Flexible Concept Bottleneck Model
Xingbo Du, Qiantong Dou, Lei Fan +1
Concept bottleneck models (CBMs) improve neural network interpretability by introducing an intermediate layer that maps human-understandable concepts to predictions. Recent work ha…
Fusionista2.0: Efficiency Retrieval System for Large-Scale Datasets
Huy M. Le, Dat Tien Nguyen, Phuc Binh Nguyen +8
The Video Browser Showdown (VBS) challenges systems to deliver accurate results under strict time constraints. To meet this demand, we present Fusionista2.0, a streamlined video re…
Leveraging Cycle-Consistent Anchor Points for Self-Supervised RGB-D Registration
Siddharth Tourani, Jayaram Reddy, Sarvesh Thakur +3
With the rise in consumer depth cameras, a wealth of unlabeled RGB-D data has become available. This prompts the question of how to utilize this data for geometric reasoning of sce…
Leveraging 2D Priors and SDF Guidance for Dynamic Urban Scene Rendering
Siddharth Tourani, Jayaram Reddy, Akash Kumbar +5
Dynamic scene rendering and reconstruction play a crucial role in computer vision and augmented reality. Recent methods based on 3D Gaussian Splatting (3DGS), have enabled accurate…
MOTOR: Multimodal Optimal Transport via Grounded Retrieval in Medical Visual Question Answering
Mai A. Shaaban, Tausifa Jan Saleem, Vijay Ram Papineni +1
Medical visual question answering (MedVQA) plays a vital role in clinical decision-making by providing contextually rich answers to image-based queries. Although vision-language mo…
Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning
Chun-Mei Feng, Kai Yu, Xinxing Xu +4
Benefited from image-text contrastive learning, pre-trained vision-language models, e.g., CLIP, allow to direct leverage texts as images (TaI) for parameter-efficient fine-tuning (…
SOAP: Style-Omniscient Animatable Portraits
Tingting Liao, Yujian Zheng, Adilbek Karmanov +4
Creating animatable 3D avatars from a single image remains challenging due to style limitations (realistic, cartoon, anime) and difficulties in handling accessories or hairstyles.…
FrogDogNet: Fourier frequency Retained visual prompt Output Guidance for Domain Generalization of CLIP in Remote Sensing
Hariseetharam Gunduboina, Muhammad Haris Khan, Biplab Banerjee
In recent years, large-scale vision-language models (VLMs) like CLIP have gained attention for their zero-shot inference using instructional text prompts. While these models excel…
Simulating Automotive Radar with Lidar and Camera Inputs
Peili Song, Dezhen Song, Yifan Yang +2
Low-cost millimeter automotive radar has received more and more attention due to its ability to handle adverse weather and lighting conditions in autonomous driving. However, the l…
Automatic Quality Assessment of First Trimester Crown-Rump-Length Ultrasound Images
Sevim Cengiz, Ibraheem Hamdi, Mohammad Yaqub
Fetal gestational age (GA) is vital clinical information that is estimated during pregnancy in order to assess fetal growth. This is usually performed by measuring the crown-rump-l…
Breaking Down the Hierarchy: A New Approach to Leukemia Classification
Ibraheem Hamdi, Hosam El-Gendy, Ahmed Sharshar +8
The complexities inherent to leukemia, multifaceted cancer affecting white blood cells, pose considerable diagnostic and treatment challenges, primarily due to reliance on laboriou…
Vision-Language Models for Edge Networks: A Comprehensive Survey
Ahmed Sharshar, Latif U. Khan, Waseem Ullah +1
Vision Large Language Models (VLMs) combine visual understanding with natural language processing, enabling tasks like image captioning, visual question answering, and video analys…
Visual-Semantic Graph Matching Net for Zero-Shot Learning
Bowen Duan, Shiming Chen, Yufei Guo +3
Zero-shot learning (ZSL) aims to leverage additional semantic information to recognize unseen classes. To transfer knowledge from seen to unseen classes, most ZSL methods often lea…
Deepfake Media Generation and Detection in the Generative AI Era: A Survey and Outlook
Florinel-Alin Croitoru, Andrei-Iulian Hiji, Vlad Hondru +7
We survey deepfake generation and detection techniques, covering all deepfake media types: image, video, audio and multimodal content. We identify various kinds of deepfakes and co…
Patch is Enough: Naturalistic Adversarial Patch against Vision-Language Pre-training Models
Dehong Kong, Siyuan Liang, Xiaopeng Zhu +2
Visual language pre-training (VLP) models have demonstrated significant success across various domains, yet they remain vulnerable to adversarial attacks. Addressing these adversar…
Long Story Short: Story-level Video Understanding from 20K Short Films
Ridouane Ghermi, Xi Wang, Vicky Kalogeiton +1
Recent developments in vision-language models have significantly advanced video understanding. Existing datasets and tasks, however, have notable limitations. Most datasets are con…
ClimateIQA: A New Dataset and Benchmark to Advance Vision-Language Models in Meteorology Anomalies Analysis
Jian Chen, Peilin Zhou, Yining Hua +7
Meteorological heatmaps play a vital role in deciphering extreme weather phenomena, yet their inherent complexities marked by irregular contours, unstructured patterns, and complex…
ViViDex: Learning Vision-based Dexterous Manipulation from Human Videos
Zerui Chen, Shizhe Chen, Etienne Arlaud +2
In this work, we aim to learn a unified vision-based policy for multi-fingered robot hands to manipulate a variety of objects in diverse poses. Though prior work has shown benefits…
MedPromptX: Grounded Multimodal Prompting for Chest X-ray Diagnosis
Mai A. Shaaban, Adnan Khan, Mohammad Yaqub
Chest X-ray images are commonly used for predicting acute and chronic cardiopulmonary conditions, but efforts to integrate them with structured clinical data face challenges due to…
Effectiveness Assessment of Recent Large Vision-Language Models
Yao Jiang, Xinyu Yan, Ge-Peng Ji +5
The advent of large vision-language models (LVLMs) represents a remarkable advance in the quest for artificial general intelligence. However, the model's effectiveness in both spec…
Semi-supervised Open-World Object Detection
Sahal Shaji Mullappilly, Abhishek Singh Gehlot, Rao Muhammad Anwer +2
Conventional open-world object detection (OWOD) problem setting first distinguishes known and unknown classes and then later incrementally learns the unknown objects when introduce…
Few and Fewer: Learning Better from Few Examples Using Fewer Base Classes
Raphael Lafargue, Yassir Bendou, Bastien Pasdeloup +4
When training data is scarce, it is common to make use of a feature extractor that has been pre-trained on a large base dataset, either by fine-tuning its parameters on the ``targe…