Assaf Singer — accepted AI-conference papers

2026

Time-to-Move: Training-Free Motion-Controlled Video Generation via Dual-Clock Denoising

Assaf Singer, Noam Rotstein, Amir Mann, Ron Kimmel, Or Litany

ICLR 2026poster

Diffusion-based video generation can create realistic videos, yet existing image and text-based conditioning fails to offer precise motion control. Prior methods for motion control typically rely on displacement-based conditioning and require model-specific fine-tuning, which is computationally expe…

Cited by 0 Source ↗code ↗Scholar ↗

2024

DINO-Tracker: Taming DINO for Self-Supervised Point Tracking in a Single Video

Narek Tumanyan*, Assaf Singer, Shai Bagon, Tali Dekel

ECCV 2024poster

"We present – a new framework for long-term dense tracking in video. The pillar of our approach is combining test-time training on a single video, with the powerful localized semantic features learned by a pre-trained DINO-ViT model. Specifically, our framework simultaneously adopts DINO’s features…

Cited by 34 Source ↗PDF ↗Scholar ↗