33 citations · 74 across the 9 of their papers we have counts for
10 papers
Diffusion Autoencoders are Scalable Image Tokenizers
Yinbo Chen, Rohit Girdhar, Xiaolong Wang +2
Tokenizing images into compact visual representations is a key step in learning efficient and high-quality image generative models. We present a simple diffusion tokenizer (DiTo) t…
Consistent Flow Distillation for Text-to-3D Generation
Runjie Yan, Yinbo Chen, Xiaolong Wang
Score Distillation Sampling (SDS) has made significant strides in distilling image-generative models for 3D generation. However, its maximum-likelihood-seeking behavior often leads…
Image Neural Field Diffusion Models
Yinbo Chen, Oliver Wang, Richard Zhang +3
Diffusion models have shown an impressive ability to model complex data distributions, with several key advantages over GANs, such as stable training, better coverage of the traini…
Visual Reinforcement Learning with Self-Supervised 3D Representations
Yanjie Ze, Nicklas Hansen, Yinbo Chen +2
A prominent approach to visual Reinforcement Learning (RL) is to learn an internal state representation using self-supervised methods, which has the potential benefit of improved s…
Transformers as Meta-Learners for Implicit Neural Representations
Yinbo Chen, Xiaolong Wang
Implicit Neural Representations (INRs) have emerged and shown their benefits over discrete representations in recent years. However, fitting an INR to the given observations usuall…
Learning Implicit Feature Alignment Function for Semantic Segmentation
Hanzhe Hu, Yinbo Chen, Jiarui Xu +4
Integrating high-level context information with low-level details is of central importance in semantic segmentation. Towards this end, most existing segmentation models apply bilin…
VideoINR: Learning Video Implicit Neural Representation for Continuous Space-Time Super-Resolution
Zeyuan Chen, Yinbo Chen, Jingwen Liu +5
Videos typically record the streaming and continuous visual data as discrete consecutive frames. Since the storage cost is expensive for videos of high fidelity, most of them are s…
Learning Continuous Image Representation with Local Implicit Image Function
Yinbo Chen, Sifei Liu, Xiaolong Wang
How to represent an image? While the visual world is presented in a continuous manner, machines store and see the images in a discrete way with 2D arrays of pixels. In this paper,…
Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning
Yinbo Chen, Zhuang Liu, Huijuan Xu +2
Meta-learning has been the most common framework for few-shot learning in recent years. It learns the model from collections of few-shot classification tasks, which is believed to…
Rethinking Knowledge Graph Propagation for Zero-Shot Learning
Michael Kampffmeyer, Yinbo Chen, Xiaodan Liang +3
Graph convolutional neural networks have recently shown great potential for the task of zero-shot learning. These models are highly sample efficient as related concepts in the grap…