Estimating depth from single RGB images and videos is of widespread interest due to its
applications in many areas, including autonomous driving, 3D reconstruction, digital …

We introduce Blink, a new benchmark for multimodal language models (LLMs) that focuses
on core visual perception abilities not found in other evaluations. Most of the Blink tasks can …

Novel view synthesis from limited observations remains a crucial and ongoing challenge. In
the realm of NeRF-based few-shot view synthesis, there is often a trade-off between the …

We introduce GeoWizard, a new generative foundation model designed for estimating
geometric attributes, eg, depth and normals, from single images. While significant research …

We present Sapiens, a family of models for four fundamental human-centric vision tasks–2D
pose estimation, body-part segmentation, depth estimation, and surface normal prediction …

As computer vision algorithms increase in capability, their applications in clinical systems
will become more pervasive. These applications include: diagnostics, such as colonoscopy …

We present a foundation model for zero-shot metric monocular depth estimation. Our model,
Depth Pro, synthesizes high-resolution depth maps with unparalleled sharpness and high …

This paper reports on the NTIRE 2024 challenge on HR Depth From images of Specular and
Transparent surfaces held in conjunction with the New Trends in Image Restoration and …

The field of 3D reconstruction from images has rapidly evolved in the past few years, first
with the introduction of Neural Radiance Field (NeRF) and more recently with 3D Gaussian …

We present Lumina-mGPT, a family of multimodal autoregressive models capable of various
vision and language tasks, particularly excelling in generating flexible photorealistic images …