Latest AI and machine learning research in universal precautions for healthcare professionals.
The recent Segment Anything Model 2 (SAM2) has demonstrated exceptional capabilities in interactive object segmentation for both images and videos. However, as a foundational model on interactive segmentation, SAM2 performs segmentation directly based on mask memory from the past six frames, leading to two significant challenges. Firstly, during inference in videos, objects may disappear since S...
Medical image segmentation is a crucial and time-consuming task in clinical care, where mask precision is extremely important. The Segment Anything Model (SAM) offers a promising approach, as it provides an interactive interface based on visual prompting and edition to refine an initial segmentation. This model has strong generalization capabilities, does not rely on predefined classes, and adap...
The perfect alignment of 3D echocardiographic images captured from various angles has improved image quality and broadened the field of view. This s...
Human image animation aims to generate human videos of given characters and backgrounds that adhere to the desired pose sequence. However, existing ...
Deep learning methods have shown promising performances in remote sensing image change detection (CD). However, existing methods usually train a dat...
Industrial Anomaly Detection (IAD) is critical for ensuring product quality by identifying defects. Traditional methods such as feature embedding an...
BACKGROUND: Hepatic fibrosis (HF) represents a pivotal stage in the progression and potential reversal of cirrhosis, underscoring the importance of ea...
The hematology analytics used for detection and classification of small blood components is a significant challenge. In particular, when objects exi...
To jointly tackle the challenges of data and node heterogeneity in decentralized learning, we propose a distributed strong lottery ticket hypothesis...
Advances in third-generation sequencing have enabled portable and real-time genomic sequencing, but real-time data processing remains a bottleneck, ...
In today's age of social media and marketing, copyright issues can be a major roadblock to the free sharing of images. Generative AI models have mad...
This paper focuses on a key challenge in visual art understanding: given an art image, the model pinpoints pixel regions that trigger a specific hum...
Zero-shot referring image segmentation aims to locate and segment the target region based on a referring expression, with the primary challenge of a...
We present MaskMark, a simple, efficient, and flexible framework for image watermarking. MaskMark has two variants: (1) MaskMark-D, which supports g...
Recent advancements in image editing have utilized large-scale multimodal models to enable intuitive, natural instruction-driven interactions. Howev...
Given a single labeled example, in-context segmentation aims to segment corresponding objects. This setting, known as one-shot segmentation in few-s...
Document Reading Order Recovery is a fundamental task in document image understanding, playing a pivotal role in enhancing Retrieval-Augmented Gener...
Remote sensing has become critical for understanding environmental dynamics, urban planning, and disaster management. However, traditional remote se...
Existing Masked Image Modeling methods apply fixed mask patterns to guide the self-supervised training. As those mask patterns resort to different c...
Text-to-image (T2I) diffusion models have achieved remarkable success in generating high-quality images from textual prompts. However, their ability...