Pith. sign in

REVIEW 8 cited by

Mixture of Diffusers for scene composition and high resolution image generation

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2302.02412 v1 pith:OQGKQK7D submitted 2023-02-05 cs.CV cs.AIcs.LG

Mixture of Diffusers for scene composition and high resolution image generation

classification cs.CV cs.AIcs.LG
keywords diffusionimagescompositiondiffusersgenerateimagemethodsmixture
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
0 comments
read the original abstract

Diffusion methods have been proven to be very effective to generate images while conditioning on a text prompt. However, and although the quality of the generated images is unprecedented, these methods seem to struggle when trying to generate specific image compositions. In this paper we present Mixture of Diffusers, an algorithm that builds over existing diffusion models to provide a more detailed control over composition. By harmonizing several diffusion processes acting on different regions of a canvas, it allows generating larger images, where the location of each object and style is controlled by a separate diffusion process.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 8 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Tiled Prompts: Overcoming Prompt Misguidance in Image and Video Super-Resolution

    cs.CV 2026-02 unverdicted novelty 7.0

    Tiled Prompts generates tile-specific text prompts for each latent tile in diffusion super-resolution to reduce errors from global prompts and improve perceptual quality.

  2. Learning a Delighting Prior for Facial Appearance Capture in the Wild

    cs.CV 2026-05 unverdicted novelty 6.0

    A delighting network trained via Dataset Latent Modulation on heterogeneous OLAT and Light Stage data enables high-quality in-the-wild facial reflectance capture from video and produces the NeRSemble-Scan dataset.

  3. Map2World: Segment Map Conditioned Text to 3D World Generation

    cs.CV 2026-05 unverdicted novelty 6.0

    Map2World produces scale-consistent 3D worlds from text and arbitrary segment maps via a detail enhancer that incorporates global structure information.

  4. CASR: A Robust Cyclic Framework for Arbitrary Large-Scale Super-Resolution with Distribution Alignment and Self-Similarity Awareness

    cs.CV 2026-02 unverdicted novelty 6.0

    CASR enables stable arbitrary-scale super-resolution by breaking extreme magnifications into cyclic in-distribution transitions with SSAM for structural distribution alignment and SARM for texture self-similarity pres...

  5. CASR: A Robust Cyclic Framework for Arbitrary Large-Scale Super-Resolution with Distribution Alignment and Self-Similarity Awareness

    cs.CV 2026-02 conditional novelty 6.0

    CASR achieves stable arbitrary-scale super-resolution by cycling a single diffusion SR model through bounded scale steps with superpixel/depth distribution alignment and cross-patch correlation consistency.

  6. InfiniteDiffusion: Bridging Learned Fidelity and Procedural Utility for Open-World Terrain Generation

    cs.CV 2025-12 unverdicted novelty 6.0

    InfiniteDiffusion adapts diffusion models to produce infinite, seed-consistent, high-fidelity terrain with procedural-noise-like access and 9x speed over prior methods.

  7. Observable Performance Does Not Fully Reflect Adaptive System Organization: A Multi-Level Analysis of Gait Dynamics Under Occlusal Constraint

    cs.LG 2026-05 unverdicted novelty 4.0

    In one Parkinson's patient, six occlusal probes produce overlapping gait scores and UMAP embeddings, so observable performance does not uniquely identify adaptive system state under VDO constraint.

  8. Observable Performance Does Not Fully Reflect Adaptive System Organization: A Multi-Level Analysis of Gait Dynamics Under Occlusal Constraint

    cs.LG 2026-05 unverdicted novelty 3.0

    In a single Parkinson's patient, gait conditions with comparable linear performance metrics showed different temporal organizations in dynamical state space and unsupervised latent embeddings when vertical occlusion d...