Ophthalmology

Interpretable Few-Shot Retinal Disease Diagnosis with Concept-Guided Prompting of Vision-Language Models

Recent advancements in deep learning have shown significant potential for classifying retinal diseases using color fundus images. However, existing works predominantly rely exclusively on image data, lack interpretability in their diagnostic decisions, and treat medical professionals primarily as annotators for ground truth labeling. To fill this gap, we implement two key strategies: extracting ...

Seeing is Understanding: Unlocking Causal Attention into Modality-Mutual Attention for Multimodal LLMs

Recent Multimodal Large Language Models (MLLMs) have demonstrated significant progress in perceiving and reasoning over multimodal inquiries, ushering in a new research era for foundation models. However, vision-language misalignment in MLLMs has emerged as a critical challenge, where the textual responses generated by these models are not factually aligned with the given text-image inputs. Exis...

TS-CGNet: Temporal-Spatial Fusion Meets Centerline-Guided Diffusion for BEV Mapping

Bird's Eye View (BEV) perception technology is crucial for autonomous driving, as it generates top-down 2D maps for environment perception, navigati...

Vision-Language Model IP Protection via Prompt-based Learning

Vision-language models (VLMs) like CLIP (Contrastive Language-Image Pre-Training) have seen remarkable success in visual recognition, highlighting t...

Are Large Vision Language Models Good Game Players?

Large Vision Language Models (LVLMs) have demonstrated remarkable abilities in understanding and reasoning about both visual and textual information...

Q-Eval-100K: Evaluating Visual Quality and Alignment Level for Text-to-Vision Content

Evaluating text-to-vision content hinges on two crucial aspects: visual quality and alignment. While significant progress has been made in developin...

Zero-Shot Sim-to-Real Visual Quadrotor Control with Hard Constraints

We present the first framework demonstrating zero-shot sim-to-real transfer of visual control policies learned in a Neural Radiance Field (NeRF) env...

Adaptive Camera Sensor for Vision Models

Domain shift remains a persistent challenge in deep-learning-based computer vision, often requiring extensive model modifications or large labeled d...

Surgical Vision World Model

Realistic and interactive surgical simulation has the potential to facilitate crucial applications, such as medical professional training and autono...

Active Alignments of Lens Systems with Reinforcement Learning

Aligning a lens system relative to an imager is a critical challenge in camera manufacturing. While optimal alignment can be mathematically computed...

Visual-RFT: Visual Reinforcement Fine-Tuning

Reinforcement Fine-Tuning (RFT) in Large Reasoning Models like OpenAI o1 learns from feedback on its answers, which is especially useful in applicat...

vS-Graphs: Integrating Visual SLAM and Situational Graphs through Multi-level Scene Understanding

Current Visual Simultaneous Localization and Mapping (VSLAM) systems often struggle to create maps that are both semantically rich and easily interp...

Why Is Spatial Reasoning Hard for VLMs? An Attention Mechanism Perspective on Focus Areas

Large Vision Language Models (VLMs) have long struggled with spatial reasoning tasks. Surprisingly, even simple spatial reasoning tasks, such as rec...

Advancing vision-language models in front-end development via data synthesis

Modern front-end (FE) development, especially when leveraging the unique features of frameworks like React and Vue, presents distinctive challenges....

Triple-Stream Deep Feature Selection with Metaheuristic Optimization and Machine Learning for Multi-Stage Hypertensive Retinopathy Diagnosis

Hypertensive retinopathy (HR) is a severe eye disease that may cause permanent vision loss if not diagnosed early. Traditional diagnostic methods ar...

SePer: Measure Retrieval Utility Through The Lens Of Semantic Perplexity Reduction

Large Language Models (LLMs) have demonstrated improved generation performance by incorporating externally retrieved knowledge, a process known as r...

RUSSO: Robust Underwater SLAM with Sonar Optimization against Visual Degradation

Visual degradation in underwater environments poses unique and significant challenges, which distinguishes underwater SLAM from popular vision-based...

UFO: A Unified Approach to Fine-grained Visual Perception via Open-ended Language Interface

Generalist models have achieved remarkable success in both language and vision-language tasks, showcasing the potential of unified modeling. However...

Comprehensive Evaluation of OCT-based Automated Segmentation of Retinal Layer, Fluid and Hyper-Reflective Foci: Impact on Diabetic Retinopathy Severity Assessment

Diabetic retinopathy (DR) is a leading cause of vision loss, requiring early and accurate assessment to prevent irreversible damage. Spectral Domain...

Tera-MIND: Tera-scale mouse brain simulation via spatial mRNA-guided diffusion

Holistic 3D modeling of molecularly defined brain structures is crucial for understanding complex brain functions. Emerging tissue profiling technol...