most citedMagic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors

75 citations · 90 across the 5 of their papers we have counts for

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cs.CV20241 cited

TrackNeRF: Bundle Adjusting NeRF from Sparse and Noisy Views via Feature Tracks

Jinjie Mai, Wenxuan Zhu, Sara Rojas +6

Neural radiance fields (NeRFs) generally require many images with accurate poses for accurate novel view synthesis, which does not reflect realistic setups where views can be spars…

cs.CV20241 cited

Vivid-ZOO: Multi-View Video Generation with Diffusion Model

Bing Li, Cheng Zheng, Wenxuan Zhu +4

While diffusion models have shown impressive performance in 2D image/video generation, diffusion-based Text-to-Multi-view-Video (T2MVid) generation remains underexplored. The new c…

cs.CV2023

Automatic Animation of Hair Blowing in Still Portrait Photos

Wenpeng Xiao, Wentao Liu, Yitong Wang +2

We propose a novel approach to animate human hair in a still portrait photo. Existing work has largely studied the animation of fluid elements such as water and fire. However, hair…

cs.CV2023

Learning to Identify Critical States for Reinforcement Learning from Videos

Haozhe Liu, Mingchen Zhuge, Bing Li +4

Recent work on deep reinforcement learning (DRL) has pointed out that algorithmic information about good policies can be extracted from offline data which lack explicit information…

cs.CV202375 cited

Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors

Guocheng Qian, Jinjie Mai, Abdullah Hamdi +8

We present Magic123, a two-stage coarse-to-fine approach for high-quality, textured 3D meshes generation from a single unposed image in the wild using both2D and 3D priors. In the…

cs.CV20235 cited

Improving GAN Training via Feature Space Shrinkage

Haozhe Liu, Wentian Zhang, Bing Li +6

Due to the outstanding capability for data generation, Generative Adversarial Networks (GANs) have attracted considerable attention in unsupervised learning. However, training GANs…