Ophthalmology

Advancing Toward a World Without Vision Loss From Diabetes: Insights From The Mary Tyler Moore Vision Initiative Symposium 2024 on Curing Vision Loss From Diabetes.

The Mary Tyler Moore Vision Initiative (MTM Vision) honors Mary Tyler Moore's commitment to ending vision loss from diabetes. Founded by Moore's husband, Dr. S. Robert Levine, MTM Vision aims to accelerate breakthroughs in diabetic retinal disease (DRD). At the MTM Vision Symposium 2024 on Curing Vision Loss from Diabetes, experts highlighted the urgent need for updated DRD staging systems, clinic...

DOPE: Dual Object Perception-Enhancement Network for Vision-and-Language Navigation

Vision-and-Language Navigation (VLN) is a challenging task where an agent must understand language instructions and navigate unfamiliar environments using visual cues. The agent must accurately locate the target based on visual information from the environment and complete tasks through interaction with the surroundings. Despite significant advancements in this field, two major limitations persi...

Zoomer: Adaptive Image Focus Optimization for Black-box MLLM

Recent advancements in multimodal large language models (MLLMs) have broadened the scope of vision-language tasks, excelling in applications like im...

Detecting and Mitigating Hateful Content in Multimodal Memes with Vision-Language Models

The rapid evolution of social media has provided enhanced communication channels for individuals to create online content, enabling them to express ...

Learning Universal User Representations Leveraging Cross-domain User Intent at Snapchat

The development of powerful user representations is a key factor in the success of recommender systems (RecSys). Online platforms employ a range of ...

Vision Transformers in Precision Agriculture: A Comprehensive Survey

Detecting plant diseases is a crucial aspect of modern agriculture, as it plays a key role in maintaining crop health and increasing overall yield. ...

Visual Text Processing: A Comprehensive Review and Unified Evaluation

Visual text is a crucial component in both document and scene images, conveying rich semantic information and attracting significant attention in th...

Black-Box Visual Prompt Engineering for Mitigating Object Hallucination in Large Vision Language Models

Large Vision Language Models (LVLMs) often suffer from object hallucination, which undermines their reliability. Surprisingly, we find that simple o...

VR-FuseNet: A Fusion of Heterogeneous Fundus Data and Explainable Deep Network for Diabetic Retinopathy Classification

Diabetic retinopathy is a severe eye condition caused by diabetes where the retinal blood vessels get damaged and can lead to vision loss and blindn...

An Evaluation of a Visual Question Answering Strategy for Zero-shot Facial Expression Recognition in Still Images

Facial expression recognition (FER) is a key research area in computer vision and human-computer interaction. Despite recent advances in deep learni...

Deep Learning Characterizes Depression and Suicidal Ideation from Eye Movements

Identifying physiological and behavioral markers for mental health conditions is a longstanding challenge in psychiatry. Depression and suicidal ide...

FedMVP: Federated Multi-modal Visual Prompt Tuning for Vision-Language Models

Textual prompt tuning adapts Vision-Language Models (e.g., CLIP) in federated learning by tuning lightweight input tokens (or prompts) on local clie...

Hydra: Marker-Free RGB-D Hand-Eye Calibration

This work presents an RGB-D imaging-based approach to marker-free hand-eye calibration using a novel implementation of the iterative closest point (...

LPVIMO-SAM: Tightly-coupled LiDAR/Polarization Vision/Inertial/Magnetometer/Optical Flow Odometry via Smoothing and Mapping

We propose a tightly-coupled LiDAR/Polarization Vision/Inertial/Magnetometer/Optical Flow Odometry via Smoothing and Mapping (LPVIMO-SAM) framework,...

MicarVLMoE: A Modern Gated Cross-Aligned Vision-Language Mixture of Experts Model for Medical Image Captioning and Report Generation

Medical image reporting (MIR) aims to generate structured clinical descriptions from radiological images. Existing methods struggle with fine-graine...

DeepAndes: A Self-Supervised Vision Foundation Model for Multi-Spectral Remote Sensing Imagery of the Andes

By mapping sites at large scales using remotely sensed data, archaeologists can generate unique insights into long-term demographic trends, inter-re...

Weaving Context Across Images: Improving Vision-Language Models through Focus-Centric Visual Chains

Vision-language models (VLMs) achieve remarkable success in single-image tasks. However, real-world scenarios often involve intricate multi-image in...

Contrastive Language-Image Learning with Augmented Textual Prompts for 3D/4D FER Using Vision-Language Model

In this paper, we introduce AffectVLM, a vision-language model designed to integrate multiviews for a semantically rich and visually comprehensive u...

Explaining Vision GNNs: A Semantic and Visual Analysis of Graph-based Image Classification

Graph Neural Networks (GNNs) have emerged as an efficient alternative to convolutional approaches for vision tasks such as image classification, lev...

VCM: Vision Concept Modeling Based on Implicit Contrastive Learning with Vision-Language Instruction Fine-Tuning

Large Vision-Language Models (LVLMs) are pivotal for real-world AI tasks like embodied intelligence due to their strong vision-language reasoning ab...