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Found 6 papers, 3 papers with code
LaDiC: Are Diffusion Models Really Inferior to Autoregressive Counterparts for Image-to-Text Generation?
Diffusion models have exhibited remarkable capabilities in text-to-image generation.
UniEdit: A Unified Tuning-Free Framework for Video Motion and Appearance Editing
Recent advances in text-guided video editing have showcased promising results in appearance editing (e. g., stylization).
TeG-DG: Textually Guided Domain Generalization for Face Anti-Spoofing
Enhancing the domain generalization performance of Face Anti-Spoofing (FAS) techniques has emerged as a research focus.
Robustness-Guided Image Synthesis for Data-Free Quantization
Quantization has emerged as a promising direction for model compression.
Towards Distribution-Agnostic Generalized Category Discovery
In this paper, we formally define a more realistic task as distribution-agnostic generalized category discovery (DA-GCD): generating fine-grained predictions for both close- and open-set classes in a long-tailed open-world setting.
On the Effectiveness of Out-of-Distribution Data in Self-Supervised Long-Tail Learning
Recent work shows that the long-tailed learning performance could be boosted by sampling extra in-domain (ID) data for self-supervised training, however, large-scale ID data which can rebalance the minority classes are expensive to collect.
