Search Results for author: Doyup Lee

Found 12 papers, 6 papers with code

Retrieval-Augmented Score Distillation for Text-to-3D Generation

1 code implementation5 Feb 2024 Junyoung Seo, Susung Hong, Wooseok Jang, Inès Hyeonsu Kim, Minseop Kwak, Doyup Lee, Seungryong Kim

We leverage the retrieved asset to incorporate its geometric prior in the variational objective and adapt the diffusion model's 2D prior toward view consistency, achieving drastic improvements in both geometry and fidelity of generated scenes.

Retrieval Text to 3D

NVS-Adapter: Plug-and-Play Novel View Synthesis from a Single Image

no code implementations12 Dec 2023 Yoonwoo Jeong, Jinwoo Lee, Chiheon Kim, Minsu Cho, Doyup Lee

Transfer learning of large-scale Text-to-Image (T2I) models has recently shown impressive potential for Novel View Synthesis (NVS) of diverse objects from a single image.

Novel View Synthesis Transfer Learning

Variational Distribution Learning for Unsupervised Text-to-Image Generation

no code implementations CVPR 2023 Minsoo Kang, Doyup Lee, Jiseob Kim, Saehoon Kim, Bohyung Han

We propose a text-to-image generation algorithm based on deep neural networks when text captions for images are unavailable during training.

Image Captioning Variational Inference +1

Towards End-to-End Generative Modeling of Long Videos with Memory-Efficient Bidirectional Transformers

1 code implementation CVPR 2023 Jaehoon Yoo, Semin Kim, Doyup Lee, Chiheon Kim, Seunghoon Hong

However, the transformers are prohibited from directly learning the long-term dependency in videos due to the quadratic complexity of self-attention, and inherently suffering from slow inference time and error propagation due to the autoregressive process.

Video Generation

Generalizable Implicit Neural Representations via Instance Pattern Composers

1 code implementation CVPR 2023 Chiheon Kim, Doyup Lee, Saehoon Kim, Minsu Cho, Wook-Shin Han

Despite recent advances in implicit neural representations (INRs), it remains challenging for a coordinate-based multi-layer perceptron (MLP) of INRs to learn a common representation across data instances and generalize it for unseen instances.


Draft-and-Revise: Effective Image Generation with Contextual RQ-Transformer

no code implementations9 Jun 2022 Doyup Lee, Chiheon Kim, Saehoon Kim, Minsu Cho, Wook-Shin Han

After code stacks in the sequence are randomly masked, Contextual RQ-Transformer is trained to infill the masked code stacks based on the unmasked contexts of the image.

Conditional Image Generation

Autoregressive Image Generation using Residual Quantization

3 code implementations CVPR 2022 Doyup Lee, Chiheon Kim, Saehoon Kim, Minsu Cho, Wook-Shin Han

However, we postulate that previous VQ cannot shorten the code sequence and generate high-fidelity images together in terms of the rate-distortion trade-off.

Conditional Image Generation Quantization

Contrastive Regularization for Semi-Supervised Learning

no code implementations17 Jan 2022 Doyup Lee, Sungwoong Kim, Ildoo Kim, Yeongjae Cheon, Minsu Cho, Wook-Shin Han

Consistency regularization on label predictions becomes a fundamental technique in semi-supervised learning, but it still requires a large number of training iterations for high performance.

Semi-Supervised Image Classification

Regularizing Attention Networks for Anomaly Detection in Visual Question Answering

no code implementations21 Sep 2020 Doyup Lee, Yeongjae Cheon, Wook-Shin Han

The results imply that cross-modal attention in VQA is important to improve not only VQA accuracy, but also the robustness to various anomalies.

Anomaly Detection Question Answering +1

Soft Labeling Affects Out-of-Distribution Detection of Deep Neural Networks

no code implementations7 Jul 2020 Doyup Lee, Yeongjae Cheon

Soft labeling becomes a common output regularization for generalization and model compression of deep neural networks.

Model Compression Out-of-Distribution Detection +1

Demand Forecasting from Spatiotemporal Data with Graph Networks and Temporal-Guided Embedding

3 code implementations26 May 2019 Doyup Lee, Suehun Jung, Yeongjae Cheon, Dongil Kim, Seungil You

TGNet learns an autoregressive model, conditioned on temporal contexts of forecasting targets from temporal-guided embedding.

Time Series Time Series Analysis

Anomaly Detection in Multivariate Non-stationary Time Series for Automatic DBMS Diagnosis

1 code implementation8 Aug 2017 Doyup Lee

In this paper, I propose an automatic DBMS diagnosis system that detects anomaly periods with abnormal DB stat metrics and finds causal events in the periods.

Anomaly Detection Management +2

Cannot find the paper you are looking for? You can Submit a new open access paper.