Adaptive Surface Normal Constraint for Geometric Estimation from Monocular Images
This article presents a new approach to learn geometries such as depth and surface normal from images….
CREMA: Multimodal Compositional Video Reasoning via Efficient Modular Adaptation and Fusion
The paper discusses CREMA, a modality-fusion framework aimed at enhancing the efficiency of multimodal compositional video reasoning….
Mamba-ND: Selective State Space Modeling for Multi-Dimensional Data
This article presents Mamba-ND, a design that extends the Mamba architecture to multi-dimensional data. Transformers, the de-facto…
ClickSAM: Fine-tuning Segment Anything Model using click prompts for ultrasound image segmentation
The Segment Anything Model (SAM) is a popular image processing tool for its segmentation accuracy, variety of…
Point-VOS: Pointing Up Video Object Segmentation
The article introduces a novel method called Point-VOS for Video Object Segmentation (VOS). Traditional VOS methods require…
Collaborative Control for Geometry-Conditioned PBR Image Generation
The paper presents a novel method for generating PBR images directly, avoiding the challenges and inaccuracies associated…
SPHINX-X: Scaling Data and Parameters for a Family of Multi-modal Large Language Models
The article introduces SPHINX-X, a Multi-modality Large Language Model (MLLM) series, which is an enhancement of the…
InstaGen: Enhancing Object Detection by Training on Synthetic Dataset
The study presents InstaGen, a novel method to enhance object detector’s ability by training on synthetic dataset…
Traditional Machine Learning Models and Bidirectional Encoder Representations From Transformer (BERT)-Based Automatic Classification of Tweets About Eating Disorders: Algorithm Development and Validation Study
The study aimed to identify machine learning models that could efficiently categorize tweets concerning eating disorders. Over…
Establishing degrees of closeness between audio recordings along different dimensions using large-scale cross-lingual models
This research focuses on understanding the information encoded in speech processing by using vector representations of speech…