AIConfPaper
← Search

Sergei Korolev

5 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

Lightweight Predictive 3D Gaussian Splats

Junli Cao, Vidit Goel, Chaoyang Wang, Anil Kag, Ju Hu, Sergei Korolev +3
ICLR 2025poster

Recent approaches representing 3D objects and scenes using Gaussian splats show increased rendering speed across a variety of platforms and devices. While rendering such representations is indeed extremely efficient, storing and transmitting them is often prohibitively expensive. To represent large-…

Cited by 3Source ↗PDF ↗code ↗Scholar ↗
2025

Towards Physical Understanding in Video Generation: A 3D Point Regularization Approach

Yunuo Chen, Junli Cao, Vidit Goel, Sergei Korolev, Chenfanfu Jiang, Jian Ren +2
NeurIPS 2025poster

We present a novel video generation framework that integrates 3-dimensional geometry and dynamic awareness. To achieve this, we augment 2D videos with 3D point trajectories and align them in pixel space. The resulting 3D-aware video dataset, PointVid, is then used to fine-tune a latent diffusion mod…

Cited by 0Source ↗Scholar ↗
2025

Wonderland: Navigating 3D Scenes from a Single Image

Hanwen Liang, Junli Cao, Vidit Goel, Guocheng Qian, Sergei Korolev, Demetri Terzopoulos +3
CVPR 2025poster

This paper addresses a challenging question: how can we efficiently create high-quality, wide-scope 3D scenes from a single arbitrary image?Existing methods face several constraints, such as requiring multi-view data, time-consuming per-scene optimization, low visual quality, and distorted reconstru…

Cited by 12Source ↗PDF ↗Scholar ↗