74 citations · 216 across the 38 of their papers we have counts for
13 papers · 1 filter
Cavia: Camera-controllable Multi-view Video Diffusion with View-Integrated Attention
Dejia Xu, Yifan Jiang, Chen Huang +5
In recent years there have been remarkable breakthroughs in image-to-video generation. However, the 3D consistency and camera controllability of generated frames have remained unso…
Atlas Gaussians Diffusion for 3D Generation
Haitao Yang, Yuan Dong, Hanwen Jiang +3
Using the latent diffusion model has proven effective in developing novel 3D generation techniques. To harness the latent diffusion model, a key challenge is designing a high-fidel…
CamCo: Camera-Controllable 3D-Consistent Image-to-Video Generation
Dejia Xu, Weili Nie, Chao Liu +4
Recently video diffusion models have emerged as expressive generative tools for high-quality video content creation readily available to general users. However, these models often…
4K4DGen: Panoramic 4D Generation at 4K Resolution
Renjie Li, Panwang Pan, Bangbang Yang +8
The blooming of virtual reality and augmented reality (VR/AR) technologies has driven an increasing demand for the creation of high-quality, immersive, and dynamic environments. Ho…
LLMGeo: Benchmarking Large Language Models on Image Geolocation In-the-wild
Zhiqiang Wang, Dejia Xu, Rana Muhammad Shahroz Khan +3
Image geolocation is a critical task in various image-understanding applications. However, existing methods often fail when analyzing challenging, in-the-wild images. Inspired by t…
Diffusion4D: Fast Spatial-temporal Consistent 4D Generation via Video Diffusion Models
Hanwen Liang, Yuyang Yin, Dejia Xu +5
The availability of large-scale multimodal datasets and advancements in diffusion models have significantly accelerated progress in 4D content generation. Most prior approaches rel…
OpenBias: Open-set Bias Detection in Text-to-Image Generative Models
Moreno D'Incà, Elia Peruzzo, Massimiliano Mancini +6
Text-to-image generative models are becoming increasingly popular and accessible to the general public. As these models see large-scale deployments, it is necessary to deeply inves…
DreamScene360: Unconstrained Text-to-3D Scene Generation with Panoramic Gaussian Splatting
Shijie Zhou, Zhiwen Fan, Dejia Xu +6
The increasing demand for virtual reality applications has highlighted the significance of crafting immersive 3D assets. We present a text-to-3D 360 scene generation pipe…
Comp4D: LLM-Guided Compositional 4D Scene Generation
Dejia Xu, Hanwen Liang, Neel P. Bhatt +4
Recent advancements in diffusion models for 2D and 3D content creation have sparked a surge of interest in generating 4D content. However, the scarcity of 3D scene datasets constra…
AGG: Amortized Generative 3D Gaussians for Single Image to 3D
Dejia Xu, Ye Yuan, Morteza Mardani +4
Given the growing need for automatic 3D content creation pipelines, various 3D representations have been studied to generate 3D objects from a single image. Due to its superior ren…
VASE: Object-Centric Appearance and Shape Manipulation of Real Videos
Elia Peruzzo, Vidit Goel, Dejia Xu +5
Recently, several works tackled the video editing task fostered by the success of large-scale text-to-image generative models. However, most of these methods holistically edit the…
Taming Mode Collapse in Score Distillation for Text-to-3D Generation
Peihao Wang, Dejia Xu, Zhiwen Fan +8
Despite the remarkable performance of score distillation in text-to-3D generation, such techniques notoriously suffer from view inconsistency issues, also known as "Janus" artifact…
SteinDreamer: Variance Reduction for Text-to-3D Score Distillation via Stein Identity
Peihao Wang, Zhiwen Fan, Dejia Xu +8
Score distillation has emerged as one of the most prevalent approaches for text-to-3D asset synthesis. Essentially, score distillation updates 3D parameters by lifting and back-pro…