Concerns with enabling computers to interpret and understand visual inputs, such as images and videos.
The paper presents a synthetic speech detector called Patched Spectrogram Synthetic Speech Detection Transformer (PS3DT). The detector converts a time domain speech signal to a mel-spectrogram and processes it in…
Continue readingLiRaFusion is a technique proposed to improve 3D object detection in autonomous vehicles by fusing LiDAR and radar data. It combines an early fusion module for joint voxel feature encoding,…
Continue readingThis paper discusses the creation of a database of 3D mesh models of real-world objects, vital for robotic simulations and applications like computer vision and AI. Traditional CAD-based methods are…
Continue readingThe article investigates the generalization capabilities of Multimodal Large Language Models (MLLMs) under out-of-distribution scenarios and domain-specific tasks. Evaluations across synthetic images, real-world distributional shifts, and specialized datasets like medical…
Continue readingThe article introduces a new dataset called DAPlankton that is aimed at developing and benchmarking domain adaptation methods for image recognition. Different imaging instruments and local differences in plankton species…
Continue readingThis research investigates using ordinal regression methods for categorizing disease severity in chest radiographs. The researchers propose a framework that divides the ordinal regression problem into three parts: a model,…
Continue readingThe paper highlights the importance of large-scale datasets for training models in industrial automation, specifically vision-based robotic grasping. It identifies issues in existing datasets, particularly in the annotation of grasp…
Continue readingThe article presents a novel approach to Low-Light Image Enhancement (LLIE) using a new trainable color space, HVI, and a decoupling network, CIDNet. Existing methods using sRGB and HSV color…
Continue readingThis paper introduces CREMA, a new and efficient modality-fusion framework designed to improve video reasoning. By leveraging existing pre-trained models, it incorporates multiple informative modalities from videos, such as optical…
Continue readingThe Segment Anything Model (SAM) is a widely used tool for image processing, but its application in ultrasound image segmentation has limitations due to the noisy nature of ultrasound images….
Continue readingLooks like you're using an ad blocker. Please support us by disabling these ad blocker.
