18 citations · 36 across the 11 of their papers we have counts for
10 papers · 1 filter
Decoupled Generative Modeling for Human-Object Interaction Synthesis
Hwanhee Jung, Seunggwan Lee, Jeongyoon Yoon +4
Synthesizing realistic human-object interaction (HOI) is essential for 3D computer vision and robotics, underpinning animation and embodied control. Existing approaches often requi…
Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective
Seunghyeon Kim, Kyeongryeol Go
Fisheye cameras introduce significant distortion and pose unique challenges to object detection models trained on conventional datasets. In this work, we propose a data-centric pip…
Cosmos-Drive-Dreams: Scalable Synthetic Driving Data Generation with World Foundation Models
Xuanchi Ren, Yifan Lu, Tianshi Cao +13
Collecting and annotating real-world data for safety-critical physical AI systems, such as Autonomous Vehicle (AV), is time-consuming and costly. It is especially challenging to ca…
Cosmos World Foundation Model Platform for Physical AI
NVIDIA, :, Niket Agarwal +76
Physical AI needs to be trained digitally first. It needs a digital twin of itself, the policy model, and a digital twin of the world, the world model. In this paper, we present th…
L4GM: Large 4D Gaussian Reconstruction Model
Jiawei Ren, Kevin Xie, Ashkan Mirzaei +8
We present L4GM, the first 4D Large Reconstruction Model that produces animated objects from a single-view video input -- in a single feed-forward pass that takes only a second. Ke…
DistillNeRF: Perceiving 3D Scenes from Single-Glance Images by Distilling Neural Fields and Foundation Model Features
Letian Wang, Seung Wook Kim, Jiawei Yang +7
We propose DistillNeRF, a self-supervised learning framework addressing the challenge of understanding 3D environments from limited 2D observations in outdoor autonomous driving sc…
EmerDiff: Emerging Pixel-level Semantic Knowledge in Diffusion Models
Koichi Namekata, Amirmojtaba Sabour, Sanja Fidler +1
Diffusion models have recently received increasing research attention for their remarkable transfer abilities in semantic segmentation tasks. However, generating fine-grained segme…
Align Your Gaussians: Text-to-4D with Dynamic 3D Gaussians and Composed Diffusion Models
Huan Ling, Seung Wook Kim, Antonio Torralba +2
Text-guided diffusion models have revolutionized image and video generation and have also been successfully used for optimization-based 3D object synthesis. Here, we instead focus…
EmerNeRF: Emergent Spatial-Temporal Scene Decomposition via Self-Supervision
Jiawei Yang, Boris Ivanovic, Or Litany +8
We present EmerNeRF, a simple yet powerful approach for learning spatial-temporal representations of dynamic driving scenes. Grounded in neural fields, EmerNeRF simultaneously capt…
WildFusion: Learning 3D-Aware Latent Diffusion Models in View Space
Katja Schwarz, Seung Wook Kim, Jun Gao +3
Modern learning-based approaches to 3D-aware image synthesis achieve high photorealism and 3D-consistent viewpoint changes for the generated images. Existing approaches represent i…