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09/12/2023
How does representation impact in-context learning: A exploration on a synthetic task
In-context learning, i.e., learning from in-context samples, is an impre...
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06/19/2023
Shape Guided Gradient Voting for Domain Generalization
Domain generalization aims to address the domain shift between training ...
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05/29/2023
Vector-based Representation is the Key: A Study on Disentanglement and Compositional Generalization
Recognizing elementary underlying concepts from observations (disentangl...
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04/26/2023
Super-NeRF: View-consistent Detail Generation for NeRF super-resolution
The neural radiance field (NeRF) achieved remarkable success in modeling...
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03/09/2023
Unifying Layout Generation with a Decoupled Diffusion Model
Layout generation aims to synthesize realistic graphic scenes consisting...
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01/31/2023
DisDiff: Unsupervised Disentanglement of Diffusion Probabilistic Models
In this paper, targeting to understand the underlying explainable factor...
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05/20/2022
Test-time Batch Normalization
Deep neural networks often suffer the data distribution shift between tr...
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05/20/2022
Visual Concepts Tokenization
Obtaining the human-like perception ability of abstracting visual concep...
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02/24/2022
Retriever: Learning Content-Style Representation as a Token-Level Bipartite Graph
This paper addresses the unsupervised learning of content-style decompos...
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05/25/2021
Understanding Mobile GUI: from Pixel-Words to Screen-Sentences
The ubiquity of mobile phones makes mobile GUI understanding an importan...
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04/02/2021
S2R-DepthNet: Learning a Generalizable Depth-specific Structural Representation
Human can infer the 3D geometry of a scene from a sketch instead of a re...
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02/21/2021
Rethinking Content and Style: Exploring Bias for Unsupervised Disentanglement
Content and style (C-S) disentanglement intends to decompose the underly...
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02/21/2021
Do Generative Models Know Disentanglement? Contrastive Learning is All You Need
Disentangled generative models are typically trained with an extra regul...
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02/20/2021
GroupifyVAE: from Group-based Definition to VAE-based Unsupervised Representation Disentanglement
The key idea of the state-of-the-art VAE-based unsupervised representati...
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04/13/2020
Blind Quality Assessment for Image Superresolution Using Deep Two-Stream Convolutional Networks
Numerous image superresolution (SR) algorithms have been proposed for re...
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10/20/2019
Moving Indoor: Unsupervised Video Depth Learning in Challenging Environments
Recently unsupervised learning of depth from videos has made remarkable ...
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10/20/2019
Unsupervised High-Resolution Depth Learning From Videos With Dual Networks
Unsupervised depth learning takes the appearance difference between a ta...
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08/04/2019