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Found 8 papers, 6 papers with code
OAH-Net: A Deep Neural Network for Hologram Reconstruction of Off-axis Digital Holographic Microscope
Off-axis digital holographic microscopy is a high-throughput, label-free imaging technology that provides three-dimensional, high-resolution information about samples, particularly useful in large-scale cellular imaging.
MiniCPM-V: A GPT-4V Level MLLM on Your Phone
The recent surge of Multimodal Large Language Models (MLLMs) has fundamentally reshaped the landscape of AI research and industry, shedding light on a promising path toward the next AI milestone.
Ranked #7 on
Multiple-choice
on Neptune-Full
CoCoCo: Improving Text-Guided Video Inpainting for Better Consistency, Controllability and Compatibility
To this end, this paper proposes a novel text-guided video inpainting model that achieves better consistency, controllability and compatibility.
Prediction of vaccination coverage level in the heterogeneous mixing population
Heterogeneity of population is a key factor in modeling the transmission of disease among the population and has huge impact on the outcome of the transmission.
MLLM-Tool: A Multimodal Large Language Model For Tool Agent Learning
Recently, the astonishing performance of large language models (LLMs) in natural language comprehension and generation tasks triggered lots of exploration of using them as central controllers to build agent systems.
Large Multilingual Models Pivot Zero-Shot Multimodal Learning across Languages
Building a competitive counterpart in other languages is highly challenging due to the low-resource nature of non-English multimodal data (i. e., lack of large-scale, high-quality image-text data).
PEVL: Position-enhanced Pre-training and Prompt Tuning for Vision-language Models
We show that PEVL enables state-of-the-art performance of detector-free VLP models on position-sensitive tasks such as referring expression comprehension and phrase grounding, and also improves the performance on position-insensitive tasks with grounded inputs.
Ranked #1 on
Visual Commonsense Reasoning
on VCR (Q-AR) test
Fine-Grained Scene Graph Generation with Data Transfer
Scene graph generation (SGG) is designed to extract (subject, predicate, object) triplets in images.
Ranked #1 on
Unbiased Scene Graph Generation
on Visual Genome
