Matches in SemOpenAlex for { <https://semopenalex.org/work/W4381587761> ?p ?o ?g. }
Showing items 1 to 71 of
71
with 100 items per page.
- W4381587761 abstract "Recognizing the activities, causing distraction, in real-world driving scenarios is critical for ensuring the safety and reliability of both drivers and pedestrians on the roadways. Conventional computer vision techniques are typically data-intensive and require a large volume of annotated training data to detect and classify various distracted driving behaviors, thereby limiting their efficiency and scalability. We aim to develop a generalized framework that showcases robust performance with access to limited or no annotated training data. Recently, vision-language models have offered large-scale visual-textual pretraining that can be adapted to task-specific learning like distracted driving activity recognition. Vision-language pretraining models, such as CLIP, have shown significant promise in learning natural language-guided visual representations. This paper proposes a CLIP-based driver activity recognition approach that identifies driver distraction from naturalistic driving images and videos. CLIP's vision embedding offers zero-shot transfer and task-based finetuning, which can classify distracted activities from driving video data. Our results show that this framework offers state-of-the-art performance on zero-shot transfer and video-based CLIP for predicting the driver's state on two public datasets. We propose both frame-based and video-based frameworks developed on top of the CLIP's visual representation for distracted driving detection and classification task and report the results." @default.
- W4381587761 created "2023-06-22" @default.
- W4381587761 creator A5004337702 @default.
- W4381587761 creator A5018571381 @default.
- W4381587761 creator A5020152686 @default.
- W4381587761 creator A5030992210 @default.
- W4381587761 creator A5037677450 @default.
- W4381587761 creator A5057041222 @default.
- W4381587761 creator A5066142047 @default.
- W4381587761 creator A5081037761 @default.
- W4381587761 date "2023-06-16" @default.
- W4381587761 modified "2023-09-25" @default.
- W4381587761 title "Vision-Language Models can Identify Distracted Driver Behavior from Naturalistic Videos" @default.
- W4381587761 doi "https://doi.org/10.48550/arxiv.2306.10159" @default.
- W4381587761 hasPublicationYear "2023" @default.
- W4381587761 type Work @default.
- W4381587761 citedByCount "0" @default.
- W4381587761 crossrefType "posted-content" @default.
- W4381587761 hasAuthorship W4381587761A5004337702 @default.
- W4381587761 hasAuthorship W4381587761A5018571381 @default.
- W4381587761 hasAuthorship W4381587761A5020152686 @default.
- W4381587761 hasAuthorship W4381587761A5030992210 @default.
- W4381587761 hasAuthorship W4381587761A5037677450 @default.
- W4381587761 hasAuthorship W4381587761A5057041222 @default.
- W4381587761 hasAuthorship W4381587761A5066142047 @default.
- W4381587761 hasAuthorship W4381587761A5081037761 @default.
- W4381587761 hasBestOaLocation W43815877611 @default.
- W4381587761 hasConcept C107457646 @default.
- W4381587761 hasConcept C119857082 @default.
- W4381587761 hasConcept C127413603 @default.
- W4381587761 hasConcept C150899416 @default.
- W4381587761 hasConcept C154945302 @default.
- W4381587761 hasConcept C169760540 @default.
- W4381587761 hasConcept C201995342 @default.
- W4381587761 hasConcept C2776378700 @default.
- W4381587761 hasConcept C2776465824 @default.
- W4381587761 hasConcept C2780451532 @default.
- W4381587761 hasConcept C41008148 @default.
- W4381587761 hasConcept C48044578 @default.
- W4381587761 hasConcept C77088390 @default.
- W4381587761 hasConcept C86803240 @default.
- W4381587761 hasConceptScore W4381587761C107457646 @default.
- W4381587761 hasConceptScore W4381587761C119857082 @default.
- W4381587761 hasConceptScore W4381587761C127413603 @default.
- W4381587761 hasConceptScore W4381587761C150899416 @default.
- W4381587761 hasConceptScore W4381587761C154945302 @default.
- W4381587761 hasConceptScore W4381587761C169760540 @default.
- W4381587761 hasConceptScore W4381587761C201995342 @default.
- W4381587761 hasConceptScore W4381587761C2776378700 @default.
- W4381587761 hasConceptScore W4381587761C2776465824 @default.
- W4381587761 hasConceptScore W4381587761C2780451532 @default.
- W4381587761 hasConceptScore W4381587761C41008148 @default.
- W4381587761 hasConceptScore W4381587761C48044578 @default.
- W4381587761 hasConceptScore W4381587761C77088390 @default.
- W4381587761 hasConceptScore W4381587761C86803240 @default.
- W4381587761 hasLocation W43815877611 @default.
- W4381587761 hasOpenAccess W4381587761 @default.
- W4381587761 hasPrimaryLocation W43815877611 @default.
- W4381587761 hasRelatedWork W3133744144 @default.
- W4381587761 hasRelatedWork W3158560638 @default.
- W4381587761 hasRelatedWork W4221034725 @default.
- W4381587761 hasRelatedWork W4224111438 @default.
- W4381587761 hasRelatedWork W4226180125 @default.
- W4381587761 hasRelatedWork W4281382123 @default.
- W4381587761 hasRelatedWork W4289655446 @default.
- W4381587761 hasRelatedWork W4308262314 @default.
- W4381587761 hasRelatedWork W4323060030 @default.
- W4381587761 hasRelatedWork W4366978873 @default.
- W4381587761 isParatext "false" @default.
- W4381587761 isRetracted "false" @default.
- W4381587761 workType "article" @default.