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This workshop was held in conjunction with ICCV 2017, Venice, Italy.
This workshop was held in conjunction with ICCV 2017, Venice, Italy.
The workshop was a big success, thank you for participating!
Date: October 23rd (PM only)
Location: Sala Magnano (Palazzo del Casinò, 2nd floor)
Invited speakers
Invited speakers
Boston University
University of Oxford, DeepMind
INRIA
Program
Program
Posters
- Multi-kernel deep learning of deep convolutional features for action recognition
- Biswa Sengupta and Yu Qian
- Temporal Tessellation: A Unified Approach for Video Analysis, ICCV 2017
- Dotan Kaufman, Gil Levi, Tal Hassner, Lior Wolf
- End-to-end Face Detection and Cast Grouping in Movies Using Erdős–Rényi Clustering, ICCV 2017
- SouYoung Jin, Hang Su, Chris Stauffer, Erik Learned-Miller
- DeepStory: Video Story QA by Deep Embedded Memory Networks, IJCAI 2017
- Kyung-Min Kim, Min-Oh Heo, Seong-Ho Choi, Byoung-Tak Zhang
- MuSM: Multimodal Sequence Memory for Video Story Question Answering
- Kyung-Min Kim, Seong-Ho Choi, Sungjae Cho, Shin-Hyung Kim, Byoung-Tak Zhang
- Character-level Inception for Visual-Semantic Embeddings
- Jônatas Wehrmann and Rodrigo C. Barros
- Attention-based CNN Matching Net
- Tzu-Chien Liu, Yu-Hsueh Wu, Hung-Yi Lee
- Audio-Visual Sentiment Analysis for Learning Emotional Arcs in Movies, ICDM 2017
- Eric Chu and Deb Roy
- Who Framed Roger Rabbit? Multiple Choice Questions Answering about Movie Plot
- Daria Dzendzik, Carl Vogel, Qun Liu
- Localizing Moments in Video with Natural Language, ICCV 2017
- Lisa Anne Hendricks, Oliver Wang, Eli Shechtman, Josef Sivic, Trevor Darrell, Bryan Russell
- MarioQA: Answering Questions by Watching Gameplay Videos, ICCV 2017
- Jonghwan Mun, Paul Hongsuck Seo, Ilchae Jung, Bohyung Han
- A Read-Write Memory Network for Movie Story Understanding, ICCV 2017
- Seil Na, Sangho Lee, Jisung Kim, Gunhee Kim
Important Dates [Deadlines extended!]
Important Dates [Deadlines extended!]
Paper submission deadline: September 25th September 15th
Paper submission deadline: September 25th September 15th
Paper acceptance notification: October 6th (earlier for papers that have already been submitted).
Paper acceptance notification: October 6th (earlier for papers that have already been submitted).
Challenge submission deadline: October 13th September 15th
Exception: LSMDC 2017 Movie Description submission deadline: October 1st
Call for challenge participation
Call for challenge participation
The workshop organizers have composed two challenges [The Large Scale Movie Description and Understanding Challenge (LSMDC) and MovieQA] based on movies and associated data sources and will run the following tasks:
- LSMDC
- Movie description
- Movie annotation and retrieval
- Movie fill-in-the-blank task
- MovieQA
- Question-answering in movies
- Video retrieval based on plot synopses sentences
We require a short report detailing your method (1 paragraph minimum). We encourage you to write up your method as a paper submission (details below) but this is not required.
Call for paper submission
Call for paper submission
The goal of this workshop is to bring together researchers working on diverse topics in the area of multimodal video, story, and language understanding, in order to obtain a better view of existing challenges and new research directions. Possible solution pathways include learning from natural language descriptions, transfer learning, reasoning across long video sequences, understanding plots, recognizing characters, taking audio and speech into account, and in general, developing better models and algorithms for understanding video and multimodal data.
We aim to have a forum around the topic of the challenges, and invite exiting submissions on topics which include but are not limited to:
- Generating descriptions for videos.
- Generating Audio Descriptions for movies.
- Multi-sentence descriptions for images and videos.
- Video retrieval given natural sentence description.
- Visual question answering for video.
- Fill-in-the blank tasks.
- Language as supervision for video understanding.
- Using textual descriptions as weak supervision for video understanding.
- Using dialogs and/or audio for video understanding.
- Understanding video and plots.
- Recognizing characters in TV series / movies.
- Novel tasks with Audio Descriptions / DVS dataset.
- Story understanding and telling.
- Deep learning and other learning approaches for video understanding, description, story modeling.
- Analysis of challenge datasets and approaches.
We welcome submissions of novel work or work which has been accepted recently elsewhere (e.g. ICCV).
Submissions should be 4-8 pages plus references. Please, send your work to lsmdc2015+17 at gmail.com
Presentation
Presentation
Accepted papers will be presented as posters; some may be selected for spotlight or oral presentations.
The challenge winners will be asked to present their work as both oral presentation and poster. Authors may request to have only title and authors’ names published on the workshop page (default is to make submitted papers public).
Contact
Contact
Please direct your inquires to: lsmdc2015+17 at gmail.com
Organizers
Organizers
Anna Rohrbach
Max Planck Institute for Informatics
Makarand Tapaswi
University of Toronto
Atousa Torabi
Disney Research
Tegan Maharaj
École Polytechnique de Montréal
Marcus Rohrbach
Facebook AI Research
Sanja Fidler
University of Toronto
Christopher Pal
École Polytechnique de Montréal
Bernt Schiele
Max Planck Institute for Informatics
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