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04/17/2023
Bootstrapping Objectness from Videos by Relaxed Common Fate and Visual Grouping
We study learning object segmentation from unlabeled videos. Humans can ...
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12/17/2022
Improving Unsupervised Video Object Segmentation with Motion-Appearance Synergy
We present IMAS, a method that segments the primary objects in videos wi...
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07/20/2022
Animation from Blur: Multi-modal Blur Decomposition with Motion Guidance
We study the challenging problem of recovering detailed motion from a si...
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06/09/2022
Extreme Masking for Learning Instance and Distributed Visual Representations
The paper presents a scalable approach for learning distributed represen...
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03/12/2022
Bringing Rolling Shutter Images Alive with Dual Reversed Distortion
Rolling shutter (RS) distortion can be interpreted as the result of pick...
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03/08/2022
A Simple Multi-Modality Transfer Learning Baseline for Sign Language Translation
This paper proposes a simple transfer learning baseline for sign languag...
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01/05/2022
Debiased Learning from Naturally Imbalanced Pseudo-Labels for Zero-Shot and Semi-Supervised Learning
This work studies the bias issue of pseudo-labeling, a natural phenomeno...
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11/22/2021
Towards Tokenized Human Dynamics Representation
For human action understanding, a popular research direction is to analy...
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11/18/2021
One-Shot Generative Domain Adaptation
This work aims at transferring a Generative Adversarial Network (GAN) pr...
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11/11/2021
The Emergence of Objectness: Learning Zero-Shot Segmentation from Videos
Humans can easily segment moving objects without knowing what they are. ...
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06/04/2021
Aligning Pretraining for Detection via Object-Level Contrastive Learning
Image-level contrastive representation learning has proven to be highly ...
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02/16/2021
Instance Localization for Self-supervised Detection Pretraining
Prior research on self-supervised learning has led to considerable progr...
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06/11/2020
What makes instance discrimination good for transfer learning?
Unsupervised visual pretraining based on the instance discrimination pre...
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04/14/2020
Distilling Localization for Self-Supervised Representation Learning
For high-level visual recognition, self-supervised learning defines and ...
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12/20/2018
Deep Metric Transfer for Label Propagation with Limited Annotated Data
We study object recognition under the constraint that each object class ...
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08/14/2018
Improving Generalization via Scalable Neighborhood Component Analysis
Current major approaches to visual recognition follow an end-to-end form...
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05/05/2018
Unsupervised Feature Learning via Non-Parametric Instance-level Discrimination
Neural net classifiers trained on data with annotated class labels can a...
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09/07/2016
Deep Markov Random Field for Image Modeling
Markov Random Fields (MRFs), a formulation widely used in generative ima...
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11/19/2015
Adjustable Bounded Rectifiers: Towards Deep Binary Representations
Binary representation is desirable for its memory efficiency, computatio...
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06/22/2014