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LucidDreamer
The dataset used in the paper is a text-to-3D generation framework, named the LucidDreamer, to distill high-fidelity textures and shapes from pretrained 2D diffusion models. -
SceneGenie: Scene Graph Guided Diffusion Models for Image Synthesis
Text-conditioned image generation has made significant progress in recent years with generative adversarial networks and more recently, diffusion models. The proposed guidance... -
Open-Sora Plan
The dataset used in this paper for text-to-video generation, consisting of short video clips. -
VideoCrafter1
The dataset used in this paper for text-to-video generation, consisting of short video clips. -
VideoCrafter2
The dataset used in this paper for text-to-video generation, consisting of short video clips. -
D-Flow: Differentiating through Flows for Controlled Generation
The dataset used in the paper D-Flow: Differentiating through Flows for Controlled Generation -
ControlNet dataset
ControlNet dataset for image generation -
MotionDiffuser: Controllable Multi-Agent Motion Prediction using Diffusion
MotionDiffuser is a learned representation for the joint distribution of future trajectories over multiple agents using diffusion models. -
CustomConcept101
The CustomConcept101 dataset is a dataset of 101 concepts across 16 broader categories, used for evaluating personalization approaches in text-to-image diffusion models. -
Accelerating Convergence of Score-Based Diffusion Models, Provably
Diffusion models, while achieving remarkable empirical performance, often suffer from low sampling speed, due to extensive function evaluations needed during the sampling phase. -
EI2 model for text-driven video editing
The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the DAVIS dataset and the Pexels website to gather face videos. -
DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models
Learning from human feedback has been shown to improve text-to-image models. These techniques first learn a reward function that captures what humans care about in the task and... -
DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Gen...
A dataset for subject-driven generation, containing 30 subjects, including objects and live subjects/pets. -
Unveiling the Truth: Exploring Human Gaze Patterns in Fake Images
A novel dataset of partially manipulated images using diffusion models and an eye-tracking experiment to record the eye movements of different observers while viewing real and... -
Diffusion-Based Hierarchical Image Steganography
The dataset used in this paper for image steganography tasks. -
SeqDiffuSeq
The dataset used in the SeqDiffuSeq paper for sequence-to-sequence text generation. -
Adding Conditional Control to Diffusion Models with Reinforcement Learning
Diffusion models are powerful generative models that allow for precise control over the characteristics of the generated samples. While these diffusion models trained on large... -
ModelScope text-to-video
The dataset used in the paper for text-to-video diffusion models
