activity
20222025
most citedNeural 3D Scene Reconstruction with the Manhattan-world Assumption

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

collaborators

6 papers

cs.CV2025

Precise Action-to-Video Generation Through Visual Action Prompts

Yuang Wang, Chao Wen, Haoyu Guo +5

We present visual action prompts, a unified action representation for action-to-video generation of complex high-DoF interactions while maintaining transferable visual dynamics acr…

cs.CV2025★ 1 cited

Towards Depth Foundation Model: Recent Trends in Vision-Based Depth Estimation

Zhen Xu, Hongyu Zhou, Sida Peng +13

Depth estimation is a fundamental task in 3D computer vision, crucial for applications such as 3D reconstruction, free-viewpoint rendering, robotics, autonomous driving, and AR/VR…

cs.CV2025

Multi-view Reconstruction via SfM-guided Monocular Depth Estimation

Haoyu Guo, He Zhu, Sida Peng +6

In this paper, we present a new method for multi-view geometric reconstruction. In recent years, large vision models have rapidly developed, performing excellently across various t…

cs.CV2024

StreetCrafter: Street View Synthesis with Controllable Video Diffusion Models

Yunzhi Yan, Zhen Xu, Haotong Lin +8

This paper aims to tackle the problem of photorealistic view synthesis from vehicle sensor data. Recent advancements in neural scene representation have achieved notable success in…

cs.CV2023

SAM-guided Graph Cut for 3D Instance Segmentation

Haoyu Guo, He Zhu, Sida Peng +4

This paper addresses the challenge of 3D instance segmentation by simultaneously leveraging 3D geometric and multi-view image information. Many previous works have applied deep lea…

cs.CV2022★ 4 cited

Neural 3D Scene Reconstruction with the Manhattan-world Assumption

Haoyu Guo, Sida Peng, Haotong Lin +4

This paper addresses the challenge of reconstructing 3D indoor scenes from multi-view images. Many previous works have shown impressive reconstruction results on textured objects,…