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05/04/2023
Tracking through Containers and Occluders in the Wild
Tracking objects with persistence in cluttered and dynamic environments ...
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03/27/2023
Object Discovery from Motion-Guided Tokens
Object discovery – separating objects from the background without manual...
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03/20/2023
Zero-1-to-3: Zero-shot One Image to 3D Object
We introduce Zero-1-to-3, a framework for changing the camera viewpoint ...
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02/07/2023
Standing Between Past and Future: Spatio-Temporal Modeling for Multi-Camera 3D Multi-Object Tracking
This work proposes an end-to-end multi-camera 3D multi-object tracking (...
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12/12/2022
Breaking the "Object" in Video Object Segmentation
The appearance of an object can be fleeting when it transforms. As eggs ...
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04/04/2022
Object Permanence Emerges in a Random Walk along Memory
This paper proposes a self-supervised objective for learning representat...
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03/18/2022
Discovering Objects that Can Move
This paper studies the problem of object discovery – separating objects ...
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04/26/2021
Heterogeneous-Agent Trajectory Forecasting Incorporating Class Uncertainty
Reasoning about the future behavior of other agents is critical to safe ...
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03/26/2021
Learning to Track with Object Permanence
Tracking by detection, the dominant approach for online multi-object tra...
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06/28/2020
Unsupervised Learning of Video Representations via Dense Trajectory Clustering
This paper addresses the task of unsupervised learning of representation...
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05/20/2020
TAO: A Large-Scale Benchmark for Tracking Any Object
For many years, multi-object tracking benchmarks have focused on a handf...
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11/29/2019
Learning Generalizable Representations via Diverse Supervision
The problem of rare category recognition has received a lot of attention...
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10/25/2019
Learning to Track Any Object
Object tracking can be formulated as "finding the right object in a vide...
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04/29/2019
A Study on Action Detection in the Wild
The recent introduction of the AVA dataset for action detection has caus...
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02/11/2019
Towards Segmenting Everything That Moves
Video analysis is the task of perceiving the world as it changes. Often,...
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12/21/2018
Learning Compositional Representations for Few-Shot Recognition
One of the key limitations of modern deep learning based approaches lies...
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12/09/2018
A Structured Model For Action Detection
A dominant paradigm for learning-based approaches in computer vision is ...
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12/01/2017
Learning to Segment Moving Objects
We study the problem of segmenting moving objects in unconstrained video...
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12/21/2016
Learning Motion Patterns in Videos
The problem of determining whether an object is in motion, irrespective ...
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03/23/2016
Weakly-Supervised Semantic Segmentation using Motion Cues
Fully convolutional neural networks (FCNNs) trained on a large number of...
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10/12/2014