1.3k citations · 1.7k across the 29 of their papers we have counts for
6 papers · 1 filter
Multi-Sentence Grounding for Long-term Instructional Video
Zeqian Li, Qirui Chen, Tengda Han +3
In this paper, we aim to establish an automatic, scalable pipeline for denoising the large-scale instructional dataset and construct a high-quality video-text dataset with multiple…
AutoAD II: The Sequel -- Who, When, and What in Movie Audio Description
Tengda Han, Max Bain, Arsha Nagrani +3
Audio Description (AD) is the task of generating descriptions of visual content, at suitable time intervals, for the benefit of visually impaired audiences. For movies, this presen…
Learning to Count without Annotations
Lukas Knobel, Tengda Han, Yuki M. Asano
While recent supervised methods for reference-based object counting continue to improve the performance on benchmark datasets, they have to rely on small datasets due to the cost a…
Open-world Text-specified Object Counting
Niki Amini-Naieni, Kiana Amini-Naieni, Tengda Han +1
Our objective is open-world object counting in images, where the target object class is specified by a text description. To this end, we propose CounTX, a class-agnostic, single-st…
AutoAD: Movie Description in Context
Tengda Han, Max Bain, Arsha Nagrani +3
The objective of this paper is an automatic Audio Description (AD) model that ingests movies and outputs AD in text form. Generating high-quality movie AD is challenging due to the…
WhisperX: Time-Accurate Speech Transcription of Long-Form Audio
Max Bain, Jaesung Huh, Tengda Han +1
Large-scale, weakly-supervised speech recognition models, such as Whisper, have demonstrated impressive results on speech recognition across domains and languages. However, their a…