Search Results for author:
Found 24 papers, 15 papers with code
InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation
Specifically, we utilize a multi-scale approach to generate video-related descriptions.
LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models
To this end, we propose LaVie, an integrated video generation framework that operates on cascaded video latent diffusion models, comprising a base T2V model, a temporal interpolation model, and a video super-resolution model.
Ranked #4 on
Text-to-Video Generation
on EvalCrafter Text-to-Video (ECTV) Dataset
(using extra training data)
VBench: Comprehensive Benchmark Suite for Video Generative Models
We will open-source VBench, including all prompts, evaluation methods, generated videos, and human preference annotations, and also include more video generation models in VBench to drive forward the field of video generation.
DG-Font: Deformable Generative Networks for Unsupervised Font Generation
Font generation is a challenging problem especially for some writing systems that consist of a large number of characters and has attracted a lot of attention in recent years.
DGFont++: Robust Deformable Generative Networks for Unsupervised Font Generation
Moreover, we introduce contrastive self-supervised learning to learn a robust style representation for fonts by understanding the similarity and dissimilarities of fonts.
Latte: Latent Diffusion Transformer for Video Generation
We propose a novel Latent Diffusion Transformer, namely Latte, for video generation.
SinSR: Diffusion-Based Image Super-Resolution in a Single Step
Extensive experiments conducted on synthetic and real-world datasets demonstrate that the proposed method can achieve comparable or even superior performance compared to both previous SOTA methods and the teacher model, in just one sampling step, resulting in a remarkable up to x10 speedup for inference.
Diff-Font: Diffusion Model for Robust One-Shot Font Generation
Specifically, a large stroke-wise dataset is constructed, and a stroke-wise diffusion model is proposed to preserve the structure and the completion of each generated character.
Brush Your Text: Synthesize Any Scene Text on Images via Diffusion Model
To tackle this problem, we propose Diff-Text, which is a training-free scene text generation framework for any language.
Cross Attention Based Style Distribution for Controllable Person Image Synthesis
In this paper, we propose a cross attention based style distribution module that computes between the source semantic styles and target pose for pose transfer.
Long-Term Rhythmic Video Soundtracker
To this end, we present Long-Term Rhythmic Video Soundtracker (LORIS), a novel framework to synthesize long-term conditional waveforms.
ConditionVideo: Training-Free Condition-Guided Text-to-Video Generation
In this work, we introduce ConditionVideo, a training-free approach to text-to-video generation based on the provided condition, video, and input text, by leveraging the power of off-the-shelf text-to-image generation methods (e. g., Stable Diffusion).
LEO: Generative Latent Image Animator for Human Video Synthesis
Our key idea is to represent motion as a sequence of flow maps in the generation process, which inherently isolate motion from appearance.
Gated-GAN: Adversarial Gated Networks for Multi-Collection Style Transfer
We propose adversarial gated networks (Gated GAN) to transfer multiple styles in a single model.
Vlogger: Make Your Dream A Vlog
More importantly, Vlogger can generate over 5-minute vlogs from open-world descriptions, without loss of video coherence on script and actor.
Attention-GAN for Object Transfiguration in Wild Images
This paper studies the object transfiguration problem in wild images.
S-OHEM: Stratified Online Hard Example Mining for Object Detection
S-OHEM exploits OHEM with stratified sampling, a widely-adopted sampling technique, to choose the training examples according to this influence during hard example mining, and thus enhance the performance of object detectors.
OCR-RTPS: An OCR-based real-time positioning system for the valet parking
Obtaining the position of ego-vehicle is a crucial prerequisite for automatic control and path planning in the field of autonomous driving.
Hierarchical Diffusion Autoencoders and Disentangled Image Manipulation
To mitigate those limitations, we propose Hierarchical Diffusion Autoencoders (HDAE) that exploit the fine-grained-to-abstract and lowlevel-to-high-level feature hierarchy for the latent space of diffusion models.
Weakly Supervised Scene Text Generation for Low-resource Languages
A large number of annotated training images is crucial for training successful scene text recognition models.
PPD: A New Valet Parking Pedestrian Fisheye Dataset for Autonomous Driving
In this paper, wepresent the Parking Pedestrian Dataset (PPD), a large-scale fisheye dataset to support research dealing with real-world pedestrians, especially with occlusions and diverse postures.
SEINE: Short-to-Long Video Diffusion Model for Generative Transition and Prediction
The goal is to generate high-quality long videos with smooth and creative transitions between scenes and varying lengths of shot-level videos.
EpiDiff: Enhancing Multi-View Synthesis via Localized Epipolar-Constrained Diffusion
Generating multiview images from a single view facilitates the rapid generation of a 3D mesh conditioned on a single image.
A flexible Bayesian g-formula for causal survival analyses with time-dependent confounding
To enhance the traditional parametric g-formula approach, we developed a more adaptable Bayesian g-formula estimator.
