COVID-19

Long-VITA: Scaling Large Multi-modal Models to 1 Million Tokens with Leading Short-Context Accuracy

We introduce Long-VITA, a simple yet effective large multi-modal model for long-context visual-language understanding tasks. It is adept at concurrently processing and analyzing modalities of image, video, and text over 4K frames or 1M tokens while delivering advanced performances on short-context multi-modal tasks. We propose an effective multi-modal training schema that starts with large langu...

The Phantom of the Elytra -- Phylogenetic Trait Extraction from Images of Rove Beetles Using Deep Learning -- Is the Mask Enough?

Phylogenetic analysis traditionally relies on labor-intensive manual extraction of morphological traits, limiting its scalability for large datasets. Recent advances in deep learning offer the potential to automate this process, but the effectiveness of different morphological representations for phylogenetic trait extraction remains poorly understood. In this study, we compare the performance o...

Realistic Image-to-Image Machine Unlearning via Decoupling and Knowledge Retention

Machine Unlearning allows participants to remove their data from a trained machine learning model in order to preserve their privacy, and security. ...

A Novel Zero-Touch, Zero-Trust, AI/ML Enablement Framework for IoT Network Security

The IoT facilitates a connected, intelligent, and sustainable society; therefore, it is imperative to protect the IoT ecosystem. The IoT-based 5G an...

Kronecker Mask and Interpretive Prompts are Language-Action Video Learners

Contrastive language-image pretraining (CLIP) has significantly advanced image-based vision learning. A pressing topic subsequently arises: how can ...

Proxy Prompt: Endowing SAM and SAM 2 with Auto-Interactive-Prompt for Medical Segmentation

In this paper, we aim to address the unmet demand for automated prompting and enhanced human-model interactions of SAM and SAM2 for the sake of prom...

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation

We tackle open-vocabulary 3D scene understanding by introducing a novel data generation pipeline and training framework. Our method addresses three ...

MATCNN: Infrared and Visible Image Fusion Method Based on Multi-scale CNN with Attention Transformer

While attention-based approaches have shown considerable progress in enhancing image fusion and addressing the challenges posed by long-range featur...

ParaSurf: a surface-based deep learning approach for paratope-antigen interaction prediction.

MOTIVATION: Identifying antibody binding sites, is crucial for developing vaccines and therapeutic antibodies, processes that are time-consuming and c...

MFP-VTON: Enhancing Mask-Free Person-to-Person Virtual Try-On via Diffusion Transformer

The garment-to-person virtual try-on (VTON) task, which aims to generate fitting images of a person wearing a reference garment, has made significan...

Human-Agent Interaction in Synthetic Social Networks: A Framework for Studying Online Polarization

Online social networks have dramatically altered the landscape of public discourse, creating both opportunities for enhanced civic participation and...

Learning Fused State Representations for Control from Multi-View Observations

Multi-View Reinforcement Learning (MVRL) seeks to provide agents with multi-view observations, enabling them to perceive environment with greater ef...

Enhancing Environmental Robustness in Few-shot Learning via Conditional Representation Learning

Few-shot learning (FSL) has recently been extensively utilized to overcome the scarcity of training data in domain-specific visual recognition. In r...

Towards Robust and Generalizable Lensless Imaging with Modular Learned Reconstruction

Lensless cameras disregard the conventional design that imaging should mimic the human eye. This is done by replacing the lens with a thin mask, and...

FCBoost-Net: A Generative Network for Synthesizing Multiple Collocated Outfits via Fashion Compatibility Boosting

Outfit generation is a challenging task in the field of fashion technology, in which the aim is to create a collocated set of fashion items that com...

SAM-guided Pseudo Label Enhancement for Multi-modal 3D Semantic Segmentation

Multi-modal 3D semantic segmentation is vital for applications such as autonomous driving and virtual reality (VR). To effectively deploy these mode...

Self-Prompt SAM: Medical Image Segmentation via Automatic Prompt SAM Adaptation

Segment Anything Model (SAM) has demonstrated impressive zero-shot performance and brought a range of unexplored capabilities to natural image segme...

TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding

fMRI (functional Magnetic Resonance Imaging) visual decoding involves decoding the original image from brain signals elicited by visual stimuli. Thi...

A Study on the Performance of U-Net Modifications in Retroperitoneal Tumor Segmentation

The retroperitoneum hosts a variety of tumors, including rare benign and malignant types, which pose diagnostic and treatment challenges due to thei...

MCM: Multi-layer Concept Map for Efficient Concept Learning from Masked Images

Masking strategies commonly employed in natural language processing are still underexplored in vision tasks such as concept learning, where conventi...