Recent developments in monocular depth estimation methods enable high-quality depth
estimation of single-view images but fail to estimate consistent video depth across different …

Realizing scaling laws in embodied AI has become a focus. However, previous work has
been scattered across diverse simulation platforms, with assets and models lacking unified …

Monocular Depth Estimation (MDE) is a fundamental computer vision task underpinning
applications such as spatial understanding, 3D reconstruction, and autonomous driving …

Learning to understand dynamic 3D scenes from imagery is crucial for applications ranging
from robotics to scene reconstruction. Yet, unlike other problems where large-scale …

Sim2real for robotic manipulation is difficult due to the challenges of simulating complex
contacts and generating realistic task distributions. To tackle the latter problem, we introduce …

In this paper, we propose VistaDream a novel framework to reconstruct a 3D scene from a
single-view image. Recent diffusion models enable generating high-quality novel-view …

Understanding the ability of humans to use objects is crucial for AI to improve daily life.
Existing studies for learning such ability focus on human-object patterns (eg, contact, spatial …

Tremendous progress has been made in deep stereo matching to excel on benchmark
datasets through per-domain fine-tuning. However, achieving strong zero-shot …

Monocular metric depth estimation (MMDE) is a crucial task to solve for indoor scene
reconstruction on edge devices. Despite this importance, existing models are sensitive to …

Diffusion models have demonstrated impressive performance in generating high-quality
videos from text prompts or images. However, precise control over the video generation …