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Vineeth Ravi

dblp:276/0088 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2024
0009-0003-0424-5531ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
2 papers
3D vision · 70% Video understanding and tracking · 23% Information extraction and text analysis · 7%
Network and information security
1 paper
Privacy and data protection · 100%
Computer graphics and multimedia
1 paper
Multimedia analysis and retrieval · 100%

Topics — the 5 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computer vision › 3D vision › 3d shape modeling
3d part assembly
0.812024
IKEA Manuals at Work: 4D Grounding of Assembly Instructions on Internet Videos · NeurIPS 2024
Computer vision › 3D vision
3d scene understanding
0.812024
IKEA Manuals at Work: 4D Grounding of Assembly Instructions on Internet Videos · NeurIPS 2024
Computer vision › 3D vision
pose estimation
0.812024
IKEA Manuals at Work: 4D Grounding of Assembly Instructions on Internet Videos · NeurIPS 2024
Computer vision › Video understanding and tracking
video object segmentation
0.812024
IKEA Manuals at Work: 4D Grounding of Assembly Instructions on Internet Videos · NeurIPS 2024
Natural language and speech › Information extraction and text analysis › sentiment analysis
complaint analysis
0.212024
Shortchanged: Uncovering and Analyzing Intimate Partner Financial Abuse in Consumer Complaints · CHI 2024

Methods — techniques the papers use, named apart from their topics

mixed-method analysis · 1.5language modeling · 1.5expert human review · 1.5dense spatio-temporal alignment · 1.5
YearPublicationVenuePosition
2024 Shortchanged: Uncovering and Analyzing Intimate Partner Financial Abuse in Consumer Complaints
abstract
Digital financial services can introduce new digital-safety risks for users, particularly survivors of intimate partner financial abuse (IPFA). To offer improved support for such users, a comprehensive understanding of their support needs and the barriers they face to redress by financial institutions is essential. Drawing from a dataset of 2.7 million customer complaints, we implement a bespoke workflow that utilizes language-modeling techniques and expert human review to identify complaints describing IPFA. Our mixed-method analysis provides insight into the most common digital financial products involved in these attacks, and the barriers consumers report encountering when doing so. Our contributions are twofold; we offer the first human-labeled dataset for this overlooked harm and provide practical implications for technical practice, research, and design for better supporting and protecting survivors of IPFA.
Arkaprabha Bhattacharya, Kevin Lee 0001, Vineeth Ravi, Jessica Staddon, Rosanna Bellini
CHI3
2024 IKEA Manuals at Work: 4D Grounding of Assembly Instructions on Internet Videos
abstract
Shape assembly is a ubiquitous task in daily life, integral for constructing complex 3D structures like IKEA furniture. While significant progress has been made in developing autonomous agents for shape assembly, existing datasets have not yet tackled the 4D grounding of assembly instructions in videos, essential for a holistic understanding of assembly in 3D space over time. We introduce IKEA Video Manuals, a dataset that features 3D models of furniture parts, instructional manuals, assembly videos from the Internet, and most importantly, annotations of dense spatio-temporal alignments between these data modalities. To demonstrate the utility of IKEA Video Manuals, we present five applications essential for shape assembly: assembly plan generation, part-conditioned segmentation, part-conditioned pose estimation, video object segmentation, and furniture assembly based on instructional video manuals. For each application, we provide evaluation metrics and baseline methods. Through experiments on our annotated data, we highlight many challenges in grounding assembly instructions in videos to improve shape assembly, including handling occlusions, varying viewpoints, and extended assembly sequences.
Yunong Liu, Cristóbal Eyzaguirre, Manling Li, Shubh Khanna, Juan Carlos Niebles, Vineeth Ravi, Saumitra Mishra, Jiajun Wu 0001
NeurIPS6