Search Results for author:
Found 7 papers, 3 papers with code
Moment Detection in Long Tutorial Videos
To study this problem, we propose the first dataset of untrimmed, long-form tutorial videos for the task of Moment Detection called the Behance Moment Detection (BMD) dataset.
Cross Modal Retrieval with Querybank Normalisation
In this work we first show that, despite their effectiveness, state-of-the-art joint embeddings suffer significantly from the longstanding "hubness problem" in which a small number of gallery embeddings form the nearest neighbours of many queries.
Ranked #5 on
Video Retrieval
on QuerYD
TEACHTEXT: CrossModal Generalized Distillation for Text-Video Retrieval
In recent years, considerable progress on the task of text-video retrieval has been achieved by leveraging large-scale pretraining on visual and audio datasets to construct powerful video encoders.
A hierarchical approach to vision-based language generation: from simple sentences to complex natural language
Automatically describing videos in natural language is an ambitious problem, which could bridge our understanding of vision and language.
Unsupervised learning of foreground object detection
We train a student deep network to predict the output of a teacher pathway that performs unsupervised object discovery in videos or large image collections.
Mining for meaning: from vision to language through multiple networks consensus
Here we propose an approach to describe videos in natural language by reaching a consensus among multiple encoder-decoder networks.
Unsupervised learning from video to detect foreground objects in single images
Our approach is different from the published literature that performs unsupervised discovery in videos or in collections of images at test time.
