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20192026
most citedLet 2D Diffusion Model Know 3D-Consistency for Robust Text-to-3D Generation

36 citations · 54 across the 19 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.CV2023

Dense Text-to-Image Generation with Attention Modulation

Yunji Kim, Jiyoung Lee, Jin-Hwa Kim +2

Existing text-to-image diffusion models struggle to synthesize realistic images given dense captions, where each text prompt provides a detailed description for a specific image re…

cs.CV2023

Hierarchical Visual Primitive Experts for Compositional Zero-Shot Learning

Hanjae Kim, Jiyoung Lee, Seongheon Park +1

Compositional zero-shot learning (CZSL) aims to recognize unseen compositions with prior knowledge of known primitives (attribute and object). Previous works for CZSL often suffer…

cs.CV2023

Dual-path Adaptation from Image to Video Transformers

Jungin Park, Jiyoung Lee, Kwanghoon Sohn

In this paper, we efficiently transfer the surpassing representation power of the vision foundation models, such as ViT and Swin, for video understanding with only a few trainable…

cs.CV2023★ 36 cited

Let 2D Diffusion Model Know 3D-Consistency for Robust Text-to-3D Generation

Junyoung Seo, Wooseok Jang, Min-Seop Kwak +6

Text-to-3D generation has shown rapid progress in recent days with the advent of score distillation, a methodology of using pretrained text-to-2D diffusion models to optimize neura…

cs.CV2023★ 1 cited

Semi-Parametric Video-Grounded Text Generation

Sungdong Kim, Jin-Hwa Kim, Jiyoung Lee +1

Efficient video-language modeling should consider the computational cost because of a large, sometimes intractable, number of video frames. Parametric approaches such as the attent…