Related papers: SPICA: Interactive Video Content Exploration throu…
Purpose: Autonomous vehicles (AVs) are becoming a promising transportation solution for blind and low-vision (BLV) travelers, offering the potential for greater independent mobility. This paper explores the information needs of BLV users…
VLA architectures that pair a pretrained VLM with a flow-matching action expert have emerged as a strong paradigm for language-conditioned manipulation. Yet the VLM, optimized for semantic abstraction and typically conditioned on static…
Visual question answering (VQA) is the task of answering questions about an image. The task assumes an understanding of both the image and the question to provide a natural language answer. VQA has gained popularity in recent years due to…
Visual Spatial Description (VSD) aims to generate texts that describe the spatial relationships between objects within images. Traditional visual spatial relationship classification (VSRC) methods typically output the spatial relationship…
Blind Image Quality Assessment (BIQA) aims to develop methods that estimate the quality scores of images in the absence of a reference image. In this paper, we approach BIQA from a distortion identification perspective, where our primary…
This paper introduces VIVRA (Voice Interactive Virtual Reality Annotation), a VR application combining multimodal interaction with large language models (LLMs) to transform users' ideas into interactive 3D visualizations. VIVRA converts…
Recent efforts in video reasoning segmentation (VRS) integrate large language models (LLMs) with perception models to localize and track objects via textual instructions, achieving barely satisfactory results in simple scenarios. However,…
Video Quality Assessment (VQA) aims to simulate the process of perceiving video quality by the human visual system (HVS). The judgments made by HVS are always influenced by human subjective feelings. However, most of the current VQA…
Current large multimodal models (LMMs) face significant challenges in processing and comprehending long-duration or high-resolution videos, which is mainly due to the lack of high-quality datasets. To address this issue from a data-centric…
Many fine-grained classification tasks, like rare animal identification, have limited training data and consequently classifiers trained on these datasets often fail to generalize to variations in the domain like changes in weather or…
Voice User Interfaces (VUIs) owing to recent developments in Artificial Intelligence (AI) and Natural Language Processing (NLP), are becoming increasingly intuitive and functional. They are especially promising for older adults, also with…
BIQA (Blind Image Quality Assessment) is an important field of study that evaluates images automatically. Although significant progress has been made, blind image quality assessment remains a difficult task since images vary in content and…
Assistive technologies for people with visual impairments (PVI) have made significant advancements, particularly with the integration of artificial intelligence (AI) and real-time sensor technologies. However, current solutions often…
Despite the growth of e-commerce, brick-and-mortar stores are still the preferred destinations for many people. In this paper, we present ISA, a mobile-based intelligent shopping assistant that is designed to improve shopping experience in…
Voice assistants have become ubiquitous in smart devices allowing users to instantly access information via voice questions. While extensive research has been conducted in question answering for voice search, little attention has been paid…
Blind and visually impaired (BVI) students face significant challenges in traditional educational settings. While screen readers and braille materials offer some accessibility, they often lack interactivity and real-time adaptability to…
While videos have become increasingly prevalent in delivering information across different educational and professional contexts, individuals with ADHD often face attention challenges when watching informational videos due to the dynamic,…
Recent advancements in adapting vision-language pre-training models like CLIP for person re-identification (ReID) tasks often rely on complex adapter design or modality-specific tuning while neglecting cross-modal interaction, leading to…
Visual Planning for Assistance (VPA) aims to predict a sequence of user actions required to achieve a specified goal based on a video showing the user's progress. Although recent advances in multimodal large language models (MLLMs) have…
The exponential growth of popularity of multimedia has led to needs for user-centric adaptive applications that manage multimedia content more effectively. Implicit analysis, which examines users' perceptual experience of multimedia by…