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20212023
most citedShuffle Transformer: Rethinking Spatial Shuffle for Vision Transformer

125 citations · 222 across the 14 of their papers we have counts for

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Showing 2023Show all

6 papers · 1 filter

cs.CV2023★ 3 cited

FaceStudio: Put Your Face Everywhere in Seconds

Yuxuan Yan, Chi Zhang, Rui Wang +5

This study investigates identity-preserving image synthesis, an intriguing task in image generation that seeks to maintain a subject's identity while adding a personalized, stylist…

cs.CV2023★ 25 cited

ChartLlama: A Multimodal LLM for Chart Understanding and Generation

Yucheng Han, Chi Zhang, Xin Chen +5

Multi-modal large language models have demonstrated impressive performances on most vision-language tasks. However, the model generally lacks the understanding capabilities for spe…

cs.CV2023

Robust Geometry-Preserving Depth Estimation Using Differentiable Rendering

Chi Zhang, Wei Yin, Gang Yu +5

In this study, we address the challenge of 3D scene structure recovery from monocular depth estimation. While traditional depth estimation methods leverage labeled datasets to dire…

cs.CV2023★ 2 cited

StableLLaVA: Enhanced Visual Instruction Tuning with Synthesized Image-Dialogue Data

Yanda Li, Chi Zhang, Gang Yu +6

The remarkable multimodal capabilities demonstrated by OpenAI's GPT-4 have sparked significant interest in the development of multimodal Large Language Models (LLMs). A primary res…

cs.CV2023★ 11 cited

Michelangelo: Conditional 3D Shape Generation based on Shape-Image-Text Aligned Latent Representation

Zibo Zhao, Wen Liu, Xin Chen +7

We present a novel alignment-before-generation approach to tackle the challenging task of generating general 3D shapes based on 2D images or texts. Directly learning a conditional…

cs.CV2023★ 13 cited

StyleAvatar3D: Leveraging Image-Text Diffusion Models for High-Fidelity 3D Avatar Generation

Chi Zhang, Yiwen Chen, Yijun Fu +7

The recent advancements in image-text diffusion models have stimulated research interest in large-scale 3D generative models. Nevertheless, the limited availability of diverse 3D r…