Latest AI and machine learning research in universal precautions for healthcare professionals.
Controllable local editing of 3D assets requires precise target localization and appropriate visual guidance. However, existing methods lack a simple yet accurate way to obtain 3D masks and struggle to achieve the desired edit while faithfully preserving the structure and appearance of non-target regions. To address these challenges, we present EditFlow3D, a training-free framework for local 3D ed...
Deepfake technologies pose increasing threats to facial privacy and identity security, motivating proactive defenses that protect facial images before misuse. Although adversarial perturbations generated by projected gradient descent (PGD) can disrupt the identity representations used by face-swapping models, their visual quality is degraded by two characteristics: perturbations are distributed br...
MLLM-based segmentation faces a core segmentation trilemma: high segmentation performance, preserved dialogue ability, and fast inference. Embedding-p...
Ask a commercial image editor to preview a cosmetic procedure and it will often change more of the face than the request names: a nose edit can also s...
Background: HIV testing is the entry point into the diagnosis, treatment and viral suppression cascade, yet in many low and middle income countries th...
Promptable segmentation foundation models (FMs) such as SAM3 and Medical SAM3 promise few-shot, interactively-specified segmentation for medical imagi...
Recent studies develop pixel-level multimodal large language models (MLLMs) that support both Region Segmentation and Region Understanding, extending ...
Despite significant advances in image segmentation, even state-of-the-art models produce masks with imperfect boundaries, semantic inconsistencies, an...
Ultrasound imaging has become increasingly widespread in clinical practice due to its portability, low cost and real-time capability, making ultrasoun...
Background and Objective: Generating realistic medical images with anatomically accurate segmentation masks helps address the shortage of annotated da...
Satellite image editing requires spatially precise object-level control, but supervised editing datasets for overhead imagery are costly to build beca...
Industrial anomaly detection and localization are limited by scarce real anomalies and pixel-level annotations, a bottleneck that synthetic image-mask...
Abstract Metagenomic sequencing can detect a broad range of pathogens, but interpreting which detections are clinically relevant requires expert adjud...
Background manipulation is a practical but under-specified image-forensics setting: the manipulated evidence can sit outside the salient foreground ob...
Sand boils, points where water seeping beneath an earthen levee re-emerges at the surface, are early warnings of internal erosion, and deep segmentati...
Remote sensing change detection aims to identify land-cover changes from bi-temporal images. Most existing methods follow a one-shot dense prediction ...
Recent generative models can produce images with few obvious visual artifacts, weakening detectors and explanations that rely only on surface appearan...
Independent sidewalk mobility is essential for blind and visually impaired pedestrians (BVIPs), yet smartphone-based assistive navigation requires per...
Interactive image segmentation is critical for efficient image annotation; however, existing methods often require many corrective clicks or rely on p...
Accurate skin lesion classification can benefit from lesion segmentation masks, but requiring masks or an auxiliary segmentation model during inferenc...