Image Comprehension
7 papers with code • 0 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Image Comprehension
Visual7W
Most implemented papers
Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models
We try to narrow the gap by mining the potential of VLMs for better performance and any-to-any workflow from three aspects, i. e., high-resolution visual tokens, high-quality data, and VLM-guided generation.
ArtGPT-4: Towards Artistic-understanding Large Vision-Language Models with Enhanced Adapter
However, a grand challenge of exploiting LLMs for multimodal learning is the size of pre-trained LLMs which are always with billions of parameters.
JourneyDB: A Benchmark for Generative Image Understanding
shihaozhaozsh/lavi-bridge
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NeurIPS 2023
On our dataset, we have devised four benchmarks to assess the performance of generated image comprehension in relation to both content and style interpretation.
Hierarchical Open-vocabulary Universal Image Segmentation
berkeley-hipie/hipie
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NeurIPS 2023
Open-vocabulary image segmentation aims to partition an image into semantic regions according to arbitrary text descriptions.
RegionBLIP: A Unified Multi-modal Pre-training Framework for Holistic and Regional Comprehension
To this end, we propose to extract features corresponding to regional objects as soft prompts for LLM, which provides a straightforward and scalable approach and eliminates the need for LLM fine-tuning.
InternLM-XComposer: A Vision-Language Large Model for Advanced Text-image Comprehension and Composition
internlm/internlm-xcomposer
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We propose InternLM-XComposer, a vision-language large model that enables advanced image-text comprehension and composition.
EarthGPT: A Universal Multi-modal Large Language Model for Multi-sensor Image Comprehension in Remote Sensing Domain
Multi-modal large language models (MLLMs) have demonstrated remarkable success in vision and visual-language tasks within the natural image domain.
