RefineAnything is a multimodal diffusion model using Focus-and-Refine crop-and-resize with blended paste-back to achieve high-fidelity local image refinement and near-perfect background preservation.
Nexus-gen: A unified model for image understanding, generation, and editing
5 Pith papers cite this work. Polarity classification is still indexing.
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HYDRA-X presents the first unified multimodal model using a single ViT for holistic image-video tokenization, with ablations on attention and compression plus a latent-level editing improvement.
InstantRetouch performs efficient high-fidelity language-guided retouching via bilateral grid prediction of affine transforms combined with variational score distillation from diffusion models.
ABACUS adapts a 3B unified foundation model using density-aware zooming, boundary-aware GRPO, and cycle-consistent self-critique to achieve SOTA on seven counting and generation benchmarks without task-specific training.
Show-o2 unifies text, image, and video understanding and generation in a single autoregressive-plus-flow-matching model built on 3D causal VAE representations.
citing papers explorer
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RefineAnything: Multimodal Region-Specific Refinement for Perfect Local Details
RefineAnything is a multimodal diffusion model using Focus-and-Refine crop-and-resize with blended paste-back to achieve high-fidelity local image refinement and near-perfect background preservation.
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HYDRA-X: Native Unified Multimodal Models with Holistic Visual Tokenizers
HYDRA-X presents the first unified multimodal model using a single ViT for holistic image-video tokenization, with ablations on attention and compression plus a latent-level editing improvement.
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InstantRetouch: Efficient and High-Fidelity Instruction-Guided Image Retouching with Bilateral Space
InstantRetouch performs efficient high-fidelity language-guided retouching via bilateral grid prediction of affine transforms combined with variational score distillation from diffusion models.
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ABACUS: Adapting Unified Foundation Model for Bridging Image Count Understanding and Generation
ABACUS adapts a 3B unified foundation model using density-aware zooming, boundary-aware GRPO, and cycle-consistent self-critique to achieve SOTA on seven counting and generation benchmarks without task-specific training.
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Show-o2: Improved Native Unified Multimodal Models
Show-o2 unifies text, image, and video understanding and generation in a single autoregressive-plus-flow-matching model built on 3D causal VAE representations.