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Found 20 papers, 17 papers with code
FreeInit: Bridging Initialization Gap in Video Diffusion Models
Though diffusion-based video generation has witnessed rapid progress, the inference results of existing models still exhibit unsatisfactory temporal consistency and unnatural dynamics.
VideoBooth: Diffusion-based Video Generation with Image Prompts
In this paper, we study the task of video generation with image prompts, which provide more accurate and direct content control beyond the text prompts.
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.
Comprehensive Overview of Bottom-up Proteomics using Mass Spectrometry
We expect this work to serve as a basic resource for new practitioners in the field of shotgun or bottom-up proteomics.
QUIZ: An Arbitrary Volumetric Point Matching Method for Medical Image Registration
Rigid pre-registration involving local-global matching or other large deformation scenarios is crucial.
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)
UnitedHuman: Harnessing Multi-Source Data for High-Resolution Human Generation
A holistic human dataset inevitably has insufficient and low-resolution information on local parts.
FreeU: Free Lunch in Diffusion U-Net
In this paper, we uncover the untapped potential of diffusion U-Net, which serves as a "free lunch" that substantially improves the generation quality on the fly.
ReliTalk: Relightable Talking Portrait Generation from a Single Video
Our key insight is to decompose the portrait's reflectance from implicitly learned audio-driven facial normals and images.
ConSlide: Asynchronous Hierarchical Interaction Transformer with Breakup-Reorganize Rehearsal for Continual Whole Slide Image Analysis
In this paper, we propose the FIRST continual learning framework for WSI analysis, named ConSlide, to tackle the challenges of enormous image size, utilization of hierarchical structure, and catastrophic forgetting by progressive model updating on multiple sequential datasets.
Collaborative Diffusion for Multi-Modal Face Generation and Editing
In this work, we present Collaborative Diffusion, where pre-trained uni-modal diffusion models collaborate to achieve multi-modal face generation and editing without re-training.
Text2Performer: Text-Driven Human Video Generation
In this work, we present Text2Performer to generate vivid human videos with articulated motions from texts.
ReVersion: Diffusion-Based Relation Inversion from Images
Specifically, we propose a novel relation-steering contrastive learning scheme to impose two critical properties of the relation prompt: 1) The relation prompt should capture the interaction between objects, enforced by the preposition prior.
Reference-based Image and Video Super-Resolution via C2-Matching
To tackle these challenges, we propose C2-Matching in this work, which performs explicit robust matching crossing transformation and resolution.
StyleFaceV: Face Video Generation via Decomposing and Recomposing Pretrained StyleGAN3
Notably, StyleFaceV is capable of generating realistic $1024\times1024$ face videos even without high-resolution training videos.
A Hybrid Deep Feature-Based Deformable Image Registration Method for Pathology Images
Deformable image registration is a necessary technique for fusing multi-modal pathology slices.
Text2Human: Text-Driven Controllable Human Image Generation
In this work, we present a text-driven controllable framework, Text2Human, for a high-quality and diverse human generation.
StyleGAN-Human: A Data-Centric Odyssey of Human Generation
In addition, a model zoo and human editing applications are demonstrated to facilitate future research in the community.
Talk-to-Edit: Fine-Grained Facial Editing via Dialog
In this work, we propose Talk-to-Edit, an interactive facial editing framework that performs fine-grained attribute manipulation through dialog between the user and the system.
Ranked #1 on
Fine-Grained Facial Editing
on CelebA-Dialog
Robust Reference-based Super-Resolution via C2-Matching
However, performing local transfer is difficult because of two gaps between input and reference images: the transformation gap (e. g. scale and rotation) and the resolution gap (e. g. HR and LR).
