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Showing papers from University of Ljubljana Show all papers

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NeurIPS 2026U TorontoHarvardMicrosoft Research New EnglandCMU, Carnegie MellonU LjubljanaDiffusion models

Test-time Scaling of Diffusions with Flow Maps

Flow Map Trajectory Tilting uses flow maps to enable principled diffusion test-time scaling with reward gradients, improving reward ascent and enabling complex image editing via vision-language models.

Amirmojtaba Sabour, Michael Albergo, Carles Domingo i Enrich, Nicholas Boffi and 3 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 6 on Hugging Face

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lenient 3/5
medium 5/10
strict 0/5
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NeurIPS 2026U TorontoNVIDIANational University of SingaporeU LjubljanaVeeda AIDiffusion models

PiD: Fast and High-Resolution Latent Decoding with Pixel Diffusion

PiD reformulates latent decoding as conditional pixel diffusion to synthesize high-resolution images with low latency and high fidelity. It decodes 512×512 latents to 2048×2048 pixels in under one second on consumer GPUs.

Yifan Lu, Qi Wu, Jay Zhangjie Wu, Zian Wang and 3 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 45 on Hugging Face

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12/20 AI panelreviewers recommend it

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AI panel: 12 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 1/5
80%Must read
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NeurIPS 2026U LjubljanaVideo understanding

UGO: Unified Architecture for General Multi-Object Tracking by Segmentation

UGO unifies GMOT via an exemplar-conditioned detection and instance-propagation architecture with consolidation and hierarchical memory, achieving state-of-the-art results.

Jer Pelhan, Alan Lukezic, Matej Kristan

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 12 of 20 reviewers recommend it
lenient 4/5
medium 6/10
strict 2/5