Yonglong Tian | DeepAI

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Wei Liu
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Xiaogang Wang
191 publications
Hongsheng Li
185 publications
Ping Luo
182 publications
Joshua B. Tenenbaum
180 publications
Wanli Ouyang
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Zhe Wang
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Cordelia Schmid
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Chen Qian
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∙ 06/26/2023

Restart Sampling for Improving Generative Processes

Generative processes that involve solving differential equations, such a...

0 Yilun Xu, et al. ∙

∙ 06/01/2023

StableRep: Synthetic Images from Text-to-Image Models Make Strong Visual Representation Learners

We investigate the potential of learning visual representations using sy...

0 Yonglong Tian, et al. ∙

∙ 05/31/2023

Improving CLIP Training with Language Rewrites

Contrastive Language-Image Pre-training (CLIP) stands as one of the most...

0 Lijie Fan, et al. ∙

∙ 02/08/2023

PFGM++: Unlocking the Potential of Physics-Inspired Generative Models

We introduce a new family of physics-inspired generative models termed P...

0 Yilun Xu, et al. ∙

∙ 10/20/2022

Does Decentralized Learning with Non-IID Unlabeled Data Benefit from Self Supervision?

Decentralized learning has been advocated and widely deployed to make ef...

0 Lirui Wang, et al. ∙

∙ 03/22/2022

Self-supervision through Random Segments with Autoregressive Coding (RandSAC)

Inspired by the success of self-supervised autoregressive representation...

1 Tianyu Hua, et al. ∙

∙ 06/23/2021

Co-advise: Cross Inductive Bias Distillation

Transformers recently are adapted from the community of natural language...

7 Sucheng Ren, et al. ∙

∙ 06/21/2021

Simple Distillation Baselines for Improving Small Self-supervised Models

While large self-supervised models have rivalled the performance of thei...

0 Jindong Gu, et al. ∙

∙ 06/09/2021

Generative Models as a Data Source for Multiview Representation Learning

Generative models are now capable of producing highly realistic images t...

15 Ali Jahanian, et al. ∙

∙ 05/17/2021

Divide and Contrast: Self-supervised Learning from Uncurated Data

Self-supervised learning holds promise in leveraging large amounts of un...

0 Yonglong Tian, et al. ∙

∙ 04/01/2021

Composable Augmentation Encoding for Video Representation Learning

We focus on contrastive methods for self-supervised video representation...

12 Chen Sun, et al. ∙

∙ 05/20/2020

What makes for good views for contrastive learning

Contrastive learning between multiple views of the data has recently ach...

16 Yonglong Tian, et al. ∙

∙ 03/25/2020

Rethinking Few-Shot Image Classification: a Good Embedding Is All You Need?

The focus of recent meta-learning research has been on the development o...

27 Yonglong Tian, et al. ∙

∙ 10/23/2019

Contrastive Representation Distillation

Often we wish to transfer representational knowledge from one neural net...

12 Yonglong Tian, et al. ∙

∙ 06/13/2019

Contrastive Multiview Coding

Humans view the world through many sensory channels, e.g., the long-wave...

1 Yonglong Tian, et al. ∙

∙ 01/09/2019

Learning to Infer and Execute 3D Shape Programs

Human perception of 3D shapes goes beyond reconstructing them as a set o...

6 Yonglong Tian, et al. ∙

∙ 06/09/2018

Representation Learning on Graphs with Jumping Knowledge Networks

Recent deep learning approaches for representation learning on graphs fo...

0 Keyulu Xu, et al. ∙

∙ 12/17/2014

DeepID-Net: Deformable Deep Convolutional Neural Networks for Object Detection

In this paper, we propose deformable deep convolutional neural networks ...

0 Wanli Ouyang, et al. ∙

∙ 11/29/2014

Pedestrian Detection aided by Deep Learning Semantic Tasks

Deep learning methods have achieved great success in pedestrian detectio...

0 Yonglong Tian, et al. ∙

∙ 09/11/2014

DeepID-Net: multi-stage and deformable deep convolutional neural networks for object detection

In this paper, we propose multi-stage and deformable deep convolutional ...

0 Wanli Ouyang, et al. ∙

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