Search Results for author: Bryan Seybold

Found 10 papers, 2 papers with code

What's in a Caption? Dataset-Specific Linguistic Diversity and Its Effect on Visual Description Models and Metrics

1 code implementation12 May 2022 David M. Chan, Austin Myers, Sudheendra Vijayanarasimhan, David A. Ross, Bryan Seybold, John F. Canny

While there have been significant gains in the field of automated video description, the generalization performance of automated description models to novel domains remains a major barrier to using these systems in the real world.

Video Description

Learning Audio-Video Modalities from Image Captions

no code implementations1 Apr 2022 Arsha Nagrani, Paul Hongsuck Seo, Bryan Seybold, Anja Hauth, Santiago Manen, Chen Sun, Cordelia Schmid

To close this gap we propose a new video mining pipeline which involves transferring captions from image captioning datasets to video clips with no additional manual effort.

Image Captioning Retrieval +4

Optical Mouse: 3D Mouse Pose From Single-View Video

no code implementations17 Jun 2021 Bo Hu, Bryan Seybold, Shan Yang, David Ross, Avneesh Sud, Graham Ruby, Yi Liu

We present a method to infer the 3D pose of mice, including the limbs and feet, from monocular videos.

Dueling Decoders: Regularizing Variational Autoencoder Latent Spaces

no code implementations17 May 2019 Bryan Seybold, Emily Fertig, Alex Alemi, Ian Fischer

Variational autoencoders learn unsupervised data representations, but these models frequently converge to minima that fail to preserve meaningful semantic information.

Unsupervised Video Object Segmentation with Motion-based Bilateral Networks

no code implementations ECCV 2018 Siyang Li, Bryan Seybold, Alexey Vorobyov, Xuejing Lei, C. -C. Jay Kuo

First, we propose a motion-based bilateral network to estimate the background based on the motion pattern of non-object regions.

Ranked #3 on Video Salient Object Detection on MCL (using extra training data)

Object Segmentation +4

Instance Embedding Transfer to Unsupervised Video Object Segmentation

no code implementations CVPR 2018 Siyang Li, Bryan Seybold, Alexey Vorobyov, Alireza Fathi, Qin Huang, C. -C. Jay Kuo

We propose a method for unsupervised video object segmentation by transferring the knowledge encapsulated in image-based instance embedding networks.

Object Optical Flow Estimation +4

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