23 citations · 29 across the 7 of their papers we have counts for
4 papers · 1 filter
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…
Align Your Flow: Scaling Continuous-Time Flow Map Distillation
Amirmojtaba Sabour, Sanja Fidler, Karsten Kreis
Diffusion- and flow-based models have emerged as state-of-the-art generative modeling approaches, but they require many sampling steps. Consistency models can distill these models…
Align Your Steps: Optimizing Sampling Schedules in Diffusion Models
Amirmojtaba Sabour, Sanja Fidler, Karsten Kreis
Diffusion models (DMs) have established themselves as the state-of-the-art generative modeling approach in the visual domain and beyond. A crucial drawback of DMs is their slow sam…
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…