Image Generation

UIP2P: Unsupervised instruction-based image editing achieves high-fidelity edits by enforcing Cycle Edit Consistency, eliminating the need for ground-truth data.

Boosting autoregressive visual generation speed by 3.6-9.5x, this research introduces parallel processing while preserving model simplicity and generation quality.

Affordance-Aware Object Insertion uses a novel Mask-Aware Dual Diffusion model & SAM-FB dataset to realistically place objects in scenes, considering contextual relationships.

FashionComposer revolutionizes fashion image creation through flexible composition of garments, faces, and poses.

ChatDiT enables zero-shot, multi-turn image generation using pretrained diffusion transformers and a novel multi-agent framework.

ColorFlow, a new AI model, accurately colorizes black-and-white image sequences while preserving character identity.

New attack fools breast ultrasound AI using subtle text prompts.

BrushEdit revolutionizes interactive image editing with instructions & inpainting.

LoRACLR merges multiple LoRA models for high-fidelity multi-concept image generation, using a contrastive objective to ensure concept distinctiveness and prevent interference.

FreeScale generates stunning 8K images and high-fidelity videos without retraining.

Edit images precisely with AI, no masks needed!

EasyRef uses multimodal LLMs to generate images from multiple references, overcoming limitations of prior methods by capturing consistent visual elements and offering improved zero-shot generalization…

DisPose disentangles pose guidance for controllable human image animation, generating diverse animations while preserving appearance consistency using only sparse skeleton pose input, eliminating the …

InvSR: a novel image super-resolution technique using diffusion inversion, enabling flexible sampling steps for efficient and high-fidelity results.

UniReal: a universal framework for image generation and editing, unifying diverse tasks via learning real-world dynamics from video data, achieving highly realistic and versatile results.

STIV: A novel, scalable method for text and image-conditioned video generation, systematically improving model architectures, training, and data curation for superior performance.

FiVA dataset and its adaptation framework enable unprecedented fine-grained control over visual attributes in text-to-image generation, empowering users to craft highly customized images.

FireFlow makes editing images faster and better.

Introducing Evaluation Agent, a faster, more flexible human-like framework for evaluating visual generative AI.

DiffSensei: A new framework generates customized manga with dynamic multi-character control using multi-modal LLMs and diffusion models, outperforming existing methods.