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06/16/2023
Learning Space-Time Semantic Correspondences
We propose a new task of space-time semantic correspondence prediction i...
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03/09/2023
Open-world Instance Segmentation: Top-down Learning with Bottom-up Supervision
Many top-down architectures for instance segmentation achieve significan...
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02/16/2023
MINOTAUR: Multi-task Video Grounding From Multimodal Queries
Video understanding tasks take many forms, from action detection to visu...
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04/12/2022
Open-World Instance Segmentation: Exploiting Pseudo Ground Truth From Learned Pairwise Affinity
Open-world instance segmentation is the task of grouping pixels into obj...
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06/17/2021
Long-Short Temporal Contrastive Learning of Video Transformers
Video transformers have recently emerged as a competitive alternative to...
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04/10/2021
Unidentified Video Objects: A Benchmark for Dense, Open-World Segmentation
Current state-of-the-art object detection and segmentation methods work ...
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12/15/2020
FLAVR: Flow-Agnostic Video Representations for Fast Frame Interpolation
A majority of approaches solve the problem of video frame interpolation ...
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11/28/2019
Self-Supervised Learning by Cross-Modal Audio-Video Clustering
The visual and audio modalities are highly correlated yet they contain d...
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06/10/2019
FASTER Recurrent Networks for Video Classification
Video classification methods often divide the video into short clips, do...
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06/10/2019
UniDual: A Unified Model for Image and Video Understanding
Although a video is effectively a sequence of images, visual perception ...
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06/07/2019
Video Modeling with Correlation Networks
Motion is a salient cue to recognize actions in video. Modern action rec...
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06/06/2019
Learning Temporal Pose Estimation from Sparsely-Labeled Videos
Modern approaches for multi-person pose estimation in video require larg...
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05/29/2019
What Makes Training Multi-Modal Networks Hard?
Consider end-to-end training of a multi-modal vs. a single-modal network...
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05/02/2019
Large-scale weakly-supervised pre-training for video action recognition
Current fully-supervised video datasets consist of only a few hundred th...
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04/08/2019
SCSampler: Sampling Salient Clips from Video for Efficient Action Recognition
While many action recognition datasets consist of collections of brief, ...
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04/04/2019
Video Classification with Channel-Separated Convolutional Networks
Group convolution has been shown to offer great computational savings in...
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01/26/2019
DistInit: Learning Video Representations without a Single Labeled Video
Video recognition models have progressed significantly over the past few...
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12/11/2018
Learning Discriminative Motion Features Through Detection
Despite huge success in the image domain, modern detection models such a...
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06/30/2018
Co-Training of Audio and Video Representations from Self-Supervised Temporal Synchronization
There is a natural correlation between the visual and auditive elements ...
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12/26/2017
Detect-and-Track: Efficient Pose Estimation in Videos
This paper addresses the problem of estimating and tracking human body k...
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11/30/2017
A Closer Look at Spatiotemporal Convolutions for Action Recognition
In this paper we discuss several forms of spatiotemporal convolutions fo...
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01/29/2017
Transformation-Based Models of Video Sequences
In this work we propose a simple unsupervised approach for next frame pr...
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06/23/2016
VideoMCC: a New Benchmark for Video Comprehension
While there is overall agreement that future technology for organizing, ...
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12/02/2014
Learning Spatiotemporal Features with 3D Convolutional Networks
We propose a simple, yet effective approach for spatiotemporal feature l...
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12/20/2013
