Towards Robust Visual Understanding: from Recognition to Reasoning
T Gokhale - Proceedings of the AAAI Conference on Artificial …, 2024 - ojs.aaai.org
Abstract Models that learn from data are widely and rapidly being deployed today for real-
world use, but they suffer from unforeseen failures due to distribution shift, adversarial …
world use, but they suffer from unforeseen failures due to distribution shift, adversarial …
VisionCam: A Comprehensive XAI Toolkit for Interpreting Image-Based Deep Learning Models
W Abdullah, A Tolba, A Elmasry… - Sustainable Machine …, 2024 - sciencesforce.com
Artificial intelligence (AI), a rapidly developing technology, has revolutionized various
aspects of our lives. However many AI models' complex inner workings are still unknown …
aspects of our lives. However many AI models' complex inner workings are still unknown …
Drml: Diagnosing and rectifying vision models using language
Recent multi-modal contrastive learning models have demonstrated the ability to learn an
embedding space suitable for building strong vision classifiers, by leveraging the rich …
embedding space suitable for building strong vision classifiers, by leveraging the rich …
AGLA: Mitigating Object Hallucinations in Large Vision-Language Models with Assembly of Global and Local Attention
Despite their great success across various multimodal tasks, Large Vision-Language
Models (LVLMs) are facing a prevalent problem with object hallucinations, where the …
Models (LVLMs) are facing a prevalent problem with object hallucinations, where the …
Mitigating object hallucinations in large vision-language models through visual contrastive decoding
Abstract Large Vision-Language Models (LVLMs) have advanced considerably intertwining
visual recognition and language understanding to generate content that is not only coherent …
visual recognition and language understanding to generate content that is not only coherent …
Comparison Visual Instruction Tuning
Comparing two images in terms of Commonalities and Differences (CaD) is a fundamental
human capability that forms the basis of advanced visual reasoning and interpretation. It is …
human capability that forms the basis of advanced visual reasoning and interpretation. It is …
Improving Just Noticeable Difference Model by Leveraging Temporal HVS Perception Characteristics
H Yin, Y Xing, G Xia, X Huang, C Yan - … , South Korea, January 5–8, 2020 …, 2020 - Springer
Temporal HVS characteristics are not fully exploited in conventional JND models. In this
paper, we improve the spatio-temporal JND model by fully leveraging the temporal HVS …
paper, we improve the spatio-temporal JND model by fully leveraging the temporal HVS …
Diffusion-based Visual Counterfactual Explanations--Towards Systematic Quantitative Evaluation
Latest methods for visual counterfactual explanations (VCE) harness the power of deep
generative models to synthesize new examples of high-dimensional images of impressive …
generative models to synthesize new examples of high-dimensional images of impressive …
[PDF][PDF] Diffusion-based Visual Counterfactual Explanations-Towards Systematic Quantitative Evaluation
AM Frühwald, B Paassen, M Gregorova - xkdd2023.isti.cnr.it
Latest methods for visual counterfactual explanations (VCE) harness the power of deep
generative models to synthesize new examples of high-dimensional images of impressive …
generative models to synthesize new examples of high-dimensional images of impressive …
Cocot: Contrastive chain-of-thought prompting for large multimodal models with multiple image inputs
When exploring the development of Artificial General Intelligence (AGI), a critical task for
these models involves interpreting and processing information from multiple image inputs …
these models involves interpreting and processing information from multiple image inputs …