Abstract This work presents Depth Anything a highly practical solution for robust monocular
depth estimation. Without pursuing novel technical modules we aim to build a simple yet …

We introduce Cambrian-1, a family of multimodal LLMs (MLLMs) designed with a vision-
centric approach. While stronger language models can enhance multimodal capabilities, the …

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 …

The three areas of realistic forward rendering, per-pixel inverse rendering, and generative
image synthesis may seem like separate and unrelated sub-fields of graphics and vision …

Novel view synthesis from a sparse set of input images is a challenging problem of great
practical interest, especially when camera poses are absent or inaccurate. Direct …

We are witnessing significant breakthroughs in the technology for generating 3D objects
from text. Existing approaches either leverage large text-to-image models to optimize a 3D …

We introduce Open-Sora Plan, an open-source project that aims to contribute a large
generation model for generating desired high-resolution videos with long durations based …

The blooming of virtual reality and augmented reality (VR/AR) technologies has driven an
increasing demand for the creation of high-quality, immersive, and dynamic environments …

We introduce LightIt a method for explicit illumination control for image generation. Recent
generative methods lack lighting control which is crucial to numerous artistic aspects of …

This paper tackles the intricate challenge of object removal to update the radiance field
using the 3D Gaussian Splatting. The main challenges of this task lie in the preservation of …