Papers Unconditional Video Generation
“Unconditional Video Generation” 태그가 달린 논문 15편 · 필터 해제
Generative Video Bi-flow
We propose a novel generative video model by robustly learning temporal change as a neural Ordinary Differential Equation (ODE) flow with a bilinear objective of combining two aspects: The first is to map from the past i…
Unconditional Video GenerationVideo GenerationRethinking Video Super-Resolution: Towards Diffusion-Based Methods without Motion Alignment
In this work, we rethink the approach to video super-resolution by introducing a method based on the Diffusion Posterior Sampling framework, combined with an unconditional video diffusion transformer operating in latent …
AllSuper-ResolutionUnconditional Video GenerationVideo Generation+1FaceVid-1K: A Large-Scale High-Quality Multiracial Human Face Video Dataset
Generating talking face videos from various conditions has recently become a highly popular research area within generative tasks. However, building a high-quality face video generation model requires a well-performing p…
Image GenerationUnconditional Video GenerationVideo GenerationStyleCineGAN: Landscape Cinemagraph Generation using a Pre-trained StyleGAN
We propose a method that can generate cinemagraphs automatically from a still landscape image using a pre-trained StyleGAN. Inspired by the success of recent unconditional video generation, we leverage a powerful pre-tra…
Unconditional Video GenerationVideo Generation0-1 laws for pattern occurrences in phylogenetic trees and networks
In a recent paper, the question of determining the fraction of binary trees that contain a fixed pattern known as the snowflake was posed. We show that this fraction goes to 1, providing two very different proofs: a pure…
10-shot image generation3D Anomaly Detection and Segmentation3D Face Reconstruction+15StyleInV: A Temporal Style Modulated Inversion Network for Unconditional Video Generation
Unconditional video generation is a challenging task that involves synthesizing high-quality videos that are both coherent and of extended duration. To address this challenge, researchers have used pretrained StyleGAN im…
Style TransferUnconditional Video GenerationVideo GenerationDDLP: Unsupervised Object-Centric Video Prediction with Deep Dynamic Latent Particles
We propose a new object-centric video prediction algorithm based on the deep latent particle (DLP) representation. In comparison to existing slot- or patch-based representations, DLPs model the scene using a set of keypo…
ObjectPositionUnconditional Video GenerationVideo Generation+1Video Diffusion Models with Local-Global Context Guidance
Diffusion models have emerged as a powerful paradigm in video synthesis tasks including prediction, generation, and interpolation. Due to the limitation of the computational budget, existing methods usually implement con…
Future predictionPredictionUnconditional Video GenerationVideo Generation+1MOSO: Decomposing MOtion, Scene and Object for Video Prediction
Motion, scene and object are three primary visual components of a video. In particular, objects represent the foreground, scenes represent the background, and motion traces their dynamics. Based on this insight, we propo…
ObjectUnconditional Video GenerationVideo Frame InterpolationVideo Generation+1MotionVideoGAN: A Novel Video Generator Based on the Motion Space Learned from Image Pairs
Video generation has achieved rapid progress benefiting from high-quality renderings provided by powerful image generators. We regard the video synthesis task as generating a sequence of images sharing the same contents …
Motion GenerationUnconditional Video GenerationVideo GenerationCelebV-HQ: A Large-Scale Video Facial Attributes Dataset
Large-scale datasets have played indispensable roles in the recent success of face generation/editing and significantly facilitated the advances of emerging research fields. However, the academic community still lacks a …
AttributeDiversityFace GenerationUnconditional Video Generation+1Video Diffusion Models
Generating temporally coherent high fidelity video is an important milestone in generative modeling research. We make progress towards this milestone by proposing a diffusion model for video generation that shows very pr…
Unconditional Video GenerationVideo GenerationVideo PredictionContinuous-Time Video Generation via Learning Motion Dynamics with Neural ODE
In order to perform unconditional video generation, we must learn the distribution of the real-world videos. In an effort to synthesize high-quality videos, various studies attempted to learn a mapping function between n…
Unconditional Video GenerationVideo GenerationDisentangled Recurrent Wasserstein Autoencoder
Learning disentangled representations leads to interpretable models and facilitates data generation with style transfer, which has been extensively studied on static data such as images in an unsupervised learning framew…
DisentanglementRepresentation LearningStyle TransferUnconditional Video Generation+1Latent Neural Differential Equations for Video Generation
Generative Adversarial Networks have recently shown promise for video generation, building off of the success of image generation while also addressing a new challenge: time. Although time was analyzed in some early work…
Unconditional Video GenerationVideo Generation