The field of visual computing is rapidly advancing due to the emergence of generative
artificial intelligence (AI), which unlocks unprecedented capabilities for the generation …

This comprehensive study evaluates the performance of OpenAI's o1-preview large
language model across a diverse array of complex reasoning tasks, spanning multiple …

Attaining a high degree of user controllability in visual generation often requires intricate,
fine-grained inputs like layouts. However, such inputs impose a substantial burden on users …

We introduce PointOdyssey, a large-scale synthetic dataset, and data generation framework,
for the training and evaluation of long-term fine-grained tracking algorithms. Our goal is to …

Being data-driven is one of the most iconic properties of deep learning algorithms. The birth
of ImageNet drives a remarkable trend of" learning from large-scale data" in computer vision …

Massive datasets and high-capacity models have driven many recent advancements in
computer vision and natural language understanding. This work presents a platform to …

We present the Habitat-Matterport 3D (HM3D) dataset. HM3D is a large-scale dataset of
1,000 building-scale 3D reconstructions from a diverse set of real-world locations. Each …

Existing image editing tools, while powerful, typically disregard the underlying 3D geometry
from which the image is projected. As a result, edits made using these tools may become …

We introduce Infinigen, a procedural generator of photorealistic 3D scenes of the natural
world. Infinigen is entirely procedural: every asset, from shape to texture, is generated from …

Existing 3D-aware image synthesis approaches mainly focus on generating a single
canonical object and show limited capacity in composing a complex scene containing a …