activity
20222024
most citedCross-Attention of Disentangled Modalities for 3D Human Mesh Recovery with Transformers

3 citations · 6 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20241 cited

MeTTA: Single-View to 3D Textured Mesh Reconstruction with Test-Time Adaptation

Kim Yu-Ji, Hyunwoo Ha, Kim Youwang +3

Reconstructing 3D from a single view image is a long-standing challenge. One of the popular approaches to tackle this problem is learning-based methods, but dealing with the test c…

cs.CV2024

FPRF: Feed-Forward Photorealistic Style Transfer of Large-Scale 3D Neural Radiance Fields

GeonU Kim, Kim Youwang, Tae-Hyun Oh

We present FPRF, a feed-forward photorealistic style transfer method for large-scale 3D neural radiance fields. FPRF stylizes large-scale 3D scenes with arbitrary, multiple style r…

cs.CV20231 cited

A Large-Scale 3D Face Mesh Video Dataset via Neural Re-parameterized Optimization

Kim Youwang, Lee Hyun, Kim Sung-Bin +3

We propose NeuFace, a 3D face mesh pseudo annotation method on videos via neural re-parameterized optimization. Despite the huge progress in 3D face reconstruction methods, generat…

cs.CV20223 cited

Cross-Attention of Disentangled Modalities for 3D Human Mesh Recovery with Transformers

Junhyeong Cho, Kim Youwang, Tae-Hyun Oh

Transformer encoder architectures have recently achieved state-of-the-art results on monocular 3D human mesh reconstruction, but they require a substantial number of parameters and…

cs.CV20221 cited

CLIP-Actor: Text-Driven Recommendation and Stylization for Animating Human Meshes

Kim Youwang, Kim Ji-Yeon, Tae-Hyun Oh

We propose CLIP-Actor, a text-driven motion recommendation and neural mesh stylization system for human mesh animation. CLIP-Actor animates a 3D human mesh to conform to a text pro…