AIConfPaper
← Search

Vladislav Shakhrai

4 accepted papers

2025

Fused View-Time Attention and Feedforward Reconstruction for 4D Scene Generation

Chaoyang Wang, Ashkan Mirzaei, Vidit Goel, Willi Menapace, Aliaksandr Siarohin, Michael Vasilkovsky +5
NeurIPS 2025poster

We propose the first framework capable of computing a 4D spatio-temporal grid of video frames and 3D Gaussian particles for each time step using a feed-forward architecture. Our architecture has two main components, a 4D video model and a 4D reconstruction model. In the first part, we analyze curren…

Cited by 0Source ↗Scholar ↗
2025

GTR: Improving Large 3D Reconstruction Models through Geometry and Texture Refinement

Peiye Zhuang, Songfang Han, Chaoyang Wang, Aliaksandr Siarohin, Jiaxu Zou, Michael Vasilkovsky +4
ICLR 2025poster

We propose a novel approach for 3D mesh reconstruction from multi-view images. We improve upon the large reconstruction model LRM that use a transformer-based triplane generator and a Neural Radiance Field (NeRF) model trained on multi-view images. We introduce three key components to significantly…

Cited by 3Source ↗PDF ↗Scholar ↗
2025

T2Bs: Text-to-Character Blendshapes via Video Generation

Jiahao Luo, Chaoyang Wang, Michael Vasilkovsky, Vladislav Shakhrai, Di Liu, Peiye Zhuang +5
ICCV 2025poster

We present T2Bs, a framework for generating high-quality, animatable character head morphable models from text by combining static text-to-3D generation with video diffusion. Text-to-3D models produce detailed static geometry but lack motion synthesis, while video diffusion models generate motion wi…

Cited by 0Source ↗PDF ↗Scholar ↗
2023

Real-Time Neural Light Field on Mobile Devices

Junli Cao, Huan Wang, Pavlo Chemerys, Vladislav Shakhrai, Ju Hu, Yun Fu +3
CVPR 2023poster

Recent efforts in Neural Rendering Fields (NeRF) have shown impressive results on novel view synthesis by utilizing implicit neural representation to represent 3D scenes. Due to the process of volumetric rendering, the inference speed for NeRF is extremely slow, limiting the application scenarios of…

Cited by 64Source ↗PDF ↗code ↗Scholar ↗