One Day Meeting: Video Understanding
Wednesday 25 September 2019
Chairs: Hilde Kuehne, Dima Damen, Juergen Gall and Ivan Laptev
Videos of Talks
On our BMVA YouTube channel there are recorded talks of the slides and speaker from the day here
Meeting Report
After the meeting the organisers prepare a short summary of the meeting.
This can be found here
Photos from the day
Below are four photos to give you a favour of the day
Programme
New models for video understanding remain a bottleneck for research despite the increase in the number of large-scale video datasets. The symposium’s objective is to share the latest research, but also feedback to the community about the major challenges, and plan for an ongoing collaboration on video understanding beyond the simplified concept of classification of trimmed videos.
The Programme can be downloaded from here.
9:00-9:45 | Keynote: Jeff Zacks | Washington University in St. Louis |
9:45-10:05 | Rahul Sukthankar | Google, CMU |
10:05-10:25 | Cees Snoek | University of Amsterdam |
10:25-10:45 | Mubarak Shah | University of Central Florida |
10:45-11:10 | Coffee Break | |
11:10-11:30 | Cordelia Schmid | INRIA |
11:30-11:50 | Dima Damen | University of Bristol |
11:50-12:10 | Juan Carlos Niebles | Stanford University - Toyota |
12:10-12:30 | Du Tran | |
12:30-12:50 | Jason Corso | University of Michigan |
12:50-14:00 | Lunch and Poster Session | |
14:00-14:20 | Andrew Zisserman | University of Oxford |
14:20-14:40 | Lorenzo Torresani | Dartmouth College, Facebook |
14:40-15:00 | Hilde Kuehne | MIT-IBM Watson Lab |
15:00-15:20 | Ivan Laptev | INRIA |
15:20-15:40 | Nazli Ikizler-Cinbis | Hacettepe University, Ankara |
15:40-16:20 | Coffee Break | |
16:20-16:40 | Jan van Gemert | Delft University of Technology |
16:40-17:00 | Juergen Gall | University of Bonn |
17:00-17:20 | Angela Yao | Singapore University |
17:20-17:40 | Efstratios Gavves | University of Amsterdam |
17:40-18:00 | Discussion and Concluding Remarks |
Venue Change
The BCS has moved, the meeting took palce at British Computer Society BCS, 25 Copthall Avenue, London EC2R 7BP
Posters:
- Pascal Mettes - University of Amsterdam: Recognizing Unseen Actions from Objects
- Xavier Giro-i-Nieto - UPC: RVOS: End-to-End RNN for Video Object Segmentation
- Tu Bui - University of Surrey: Tamper-proofing Video using Temporal Hashes on the Blockchain
- Samuel Albanie - University of Oxford: Use What You Have: Video retrieval using representations from collaborative experts
- Matthew Bezdek - Washington University: The 3D Extended Activity Multi-camera Dataset (TEAM)
- Armin Mustafa - Uni of Surrey: Semantic Co-segmentation & 4D Reconstruction for Dynamic Scene
- Luowei Zhou - University of Michigan: Grounded Video Description
- Davide Moltisanti - Uni of Bristol: Action Rec. from Single Timestamp in Untrimmed Videos
- Salah Al-Obaidi - University of Sheffield: Temporal Salience Based Human Action Recognition
- Farnoosh Heidarivincheh – Uni of Bristol: Action Completion: A Temporal Model for Moment
- Noureldien Hussein - Uni of Amsterdam: Timeception for Complex Action Recognition
- Michael Wray - University of Bristol: Learning Visual Actions Using Multiple Verb-Only Labels
- Chien-Yi Chang - Stanford University: Procedure Planning in Instructional Video
- Hazel Doughty - Uni of Bristol: Rank-aware Temporal Attention for Skill Determination in Videos
- Mohsen Fayyaz - University of Bonn: Holistic Large Scale Video Understanding
- Rami Ben-Ari - IBM Research-AI: Object detection without labeling from video with transcripts
- Yaser Souri - University of Bonn: Weakly Supervised Action Segmentation Using Mutual Consistency
- Evangelos Kazakos - University of Bristol: Audio-Visual Temporal Binding for Egocentric Action Rec.
- Jiaojiao Zhao - University of Amsterdam: Two-in-one Stream Action Detection
- Will Price - University of Bristol: Benchmarking action recognition models on EPIC-Kitchens
- Lilli Bruckschen - University of Bonn: Detection of Human-Object Interactions in Video Streams
- Jonathan Munro - Uni of Bristol: Multi-Modal Domain Adaptation for Fine-grained Action Rec.
- Anna Kukleva - Uni of Bonn: Unsupervised learning of action with continuous temporal embedding
- Aishah alsehaim - Durham Uni: Advance Visual Sequence Learning for Action Rec. via 3D-CNN
- Harri Taylor - Cardiff Uni: Audio-visual explanations for activity rec. using discriminative relevance
- Liam Hiley - Cardiff Uni: Temporal Information in Activity Rec. for Situational Understanding
- Zheheng Jiang : Context-aware Mouse Behaviour Recognition using Hidden Markov Models