Search Results for author:
Found 15 papers, 6 papers with code
CT2C-QA: Multimodal Question Answering over Chinese Text, Table and Chart
Most existing researches in MMQA only focus on two modalities such as image-text QA, table-text QA and chart-text QA, and there remains a notable scarcity in studies that investigate the joint analysis of text, tables, and charts.
A Medical Multimodal Large Language Model for Pediatric Pneumonia
This dataset comprised 2D chest X-ray images, 3D chest CT images, corresponding radiology reports, and outpatient and inpatient records.
M2NO: Multiresolution Operator Learning with Multiwavelet-based Algebraic Multigrid Method
Solving partial differential equations (PDEs) effectively necessitates a multi-scale approach, particularly critical in high-dimensional scenarios characterized by increasing grid points or resolution.
Anatomical Structure-Guided Medical Vision-Language Pre-training
For finding and existence, we regard them as image tags, applying an image-tag recognition decoder to associate image features with their respective tags within each sample and constructing soft labels for contrastive learning to improve the semantic association of different image-report pairs.
Let All be Whitened: Multi-teacher Distillation for Efficient Visual Retrieval
Instead of crafting a new method pursuing further improvement on accuracy, in this paper we propose a multi-teacher distillation framework Whiten-MTD, which is able to transfer knowledge from off-the-shelf pre-trained retrieval models to a lightweight student model for efficient visual retrieval.
Large Language Models are Complex Table Parsers
With the Generative Pre-trained Transformer 3. 5 (GPT-3. 5) exhibiting remarkable reasoning and comprehension abilities in Natural Language Processing (NLP), most Question Answering (QA) research has primarily centered around general QA tasks based on GPT, neglecting the specific challenges posed by Complex Table QA.
Enhanced Knowledge Injection for Radiology Report Generation
Automatic generation of radiology reports holds crucial clinical value, as it can alleviate substantial workload on radiologists and remind less experienced ones of potential anomalies.
Learning Segment Similarity and Alignment in Large-Scale Content Based Video Retrieval
SSAN is based on two newly proposed modules in video retrieval: (1) An efficient Self-supervised Keyframe Extraction (SKE) module to reduce redundant frame features, (2) A robust Similarity Pattern Detection (SPD) module for temporal alignment.
Video Infringement Detection via Feature Disentanglement and Mutual Information Maximization
We theoretically analyzed the mutual information between the label and the disentangled features, arriving at a loss that maximizes the extraction of task-relevant information from the original feature.
Web Photo Source Identification based on Neural Enhanced Camera Fingerprint
With the growing popularity of smartphone photography in recent years, web photos play an increasingly important role in all walks of life.
Boosting COVID-19 Severity Detection with Infection-aware Contrastive Mixup Classification
In our approach, we devise a novel infection-aware 3D Contrastive Mixup Classification network for severity grading.
CMC v2: Towards More Accurate COVID-19 Detection with Discriminative Video Priors
This paper presents our solution for the 2nd COVID-19 Competition, occurring in the framework of the AIMIA Workshop at the European Conference on Computer Vision (ECCV 2022).
TransVCL: Attention-enhanced Video Copy Localization Network with Flexible Supervision
Previous methods typically start from frame-to-frame similarity matrix generated by cosine similarity between frame-level features of the input video pair, and then detect and refine the boundaries of copied segments on similarity matrix under temporal constraints.
IDEA: Increasing Text Diversity via Online Multi-Label Recognition for Vision-Language Pre-training
However, the image-text pairs co-occurrent on the Internet typically lack explicit alignment information, which is suboptimal for VLP.
A Large-scale Comprehensive Dataset and Copy-overlap Aware Evaluation Protocol for Segment-level Video Copy Detection
In this paper, we introduce VCSL (Video Copy Segment Localization), a new comprehensive segment-level annotated video copy dataset.
