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Found 25 papers, 20 papers with code
Make-Your-Video: Customized Video Generation Using Textual and Structural Guidance
Our method, dubbed Make-Your-Video, involves joint-conditional video generation using a Latent Diffusion Model that is pre-trained for still image synthesis and then promoted for video generation with the introduction of temporal modules.
Inserting Anybody in Diffusion Models via Celeb Basis
Empowered by the proposed celeb basis, the new identity in our customized model showcases a better concept combination ability than previous personalization methods.
Explicit Visual Prompting for Universal Foreground Segmentations
We take inspiration from the widely-used pre-training and then prompt tuning protocols in NLP and propose a new visual prompting model, named Explicit Visual Prompting (EVP).
TaleCrafter: Interactive Story Visualization with Multiple Characters
Accurate Story visualization requires several necessary elements, such as identity consistency across frames, the alignment between plain text and visual content, and a reasonable layout of objects in images.
Follow Your Pose: Pose-Guided Text-to-Video Generation using Pose-Free Videos
Generating text-editable and pose-controllable character videos have an imperious demand in creating various digital human.
Explicit Visual Prompting for Low-Level Structure Segmentations
Different from the previous visual prompting which is typically a dataset-level implicit embedding, our key insight is to enforce the tunable parameters focusing on the explicit visual content from each individual image, i. e., the features from frozen patch embeddings and the input's high-frequency components.
FateZero: Fusing Attentions for Zero-shot Text-based Video Editing
We also have a better zero-shot shape-aware editing ability based on the text-to-video model.
CoordFill: Efficient High-Resolution Image Inpainting via Parameterized Coordinate Querying
Thanks to the proposed structure, we only encode the high-resolution image in a relatively low resolution for larger reception field capturing.
DPE: Disentanglement of Pose and Expression for General Video Portrait Editing
In this paper, we introduce a novel self-supervised disentanglement framework to decouple pose and expression without 3DMMs and paired data, which consists of a motion editing module, a pose generator, and an expression generator.
T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations
Additionally, we conduct analyses on HumanML3D and observe that the dataset size is a limitation of our approach.
Ranked #1 on
Motion Synthesis
on HumanML3D
CodeTalker: Speech-Driven 3D Facial Animation with Discrete Motion Prior
In this paper, we propose to cast speech-driven facial animation as a code query task in a finite proxy space of the learned codebook, which effectively promotes the vividness of the generated motions by reducing the cross-modal mapping uncertainty.
Generating Human Motion From Textual Descriptions With Discrete Representations
Additionally, we conduct analyses on HumanML3D and observe that the dataset size is a limitation of our approach.
3D GAN Inversion with Facial Symmetry Prior
It is natural to associate 3D GANs with GAN inversion methods to project a real image into the generator's latent space, allowing free-view consistent synthesis and editing, referred as 3D GAN inversion.
ShaDocNet: Learning Spatial-Aware Tokens in Transformer for Document Shadow Removal
Shadow removal improves the visual quality and legibility of digital copies of documents.
VideoReTalking: Audio-based Lip Synchronization for Talking Head Video Editing In the Wild
Our system disentangles this objective into three sequential tasks: (1) face video generation with a canonical expression; (2) audio-driven lip-sync; and (3) face enhancement for improving photo-realism.
SadTalker: Learning Realistic 3D Motion Coefficients for Stylized Audio-Driven Single Image Talking Face Animation
We present SadTalker, which generates 3D motion coefficients (head pose, expression) of the 3DMM from audio and implicitly modulates a novel 3D-aware face render for talking head generation.
Learning Enriched Illuminants for Cross and Single Sensor Color Constancy
Color constancy aims to restore the constant colors of a scene under different illuminants.
StyleHEAT: One-Shot High-Resolution Editable Talking Face Generation via Pre-trained StyleGAN
Our framework elevates the resolution of the synthesized talking face to 1024*1024 for the first time, even though the training dataset has a lower resolution.
Spatial-Separated Curve Rendering Network for Efficient and High-Resolution Image Harmonization
To this end, we propose a novel spatial-separated curve rendering network(S$^2$CRNet) for efficient and high-resolution image harmonization for the first time.
Ranked #7 on
Image Harmonization
on iHarmony4
Uformer: A General U-Shaped Transformer for Image Restoration
Powered by these two designs, Uformer enjoys a high capability for capturing both local and global dependencies for image restoration.
Ranked #1 on
Deblurring
on RealBlur-R (trained on GoPro)
Split then Refine: Stacked Attention-guided ResUNets for Blind Single Image Visible Watermark Removal
Simultaneously, to increase the robustness of watermark, attacking technique, such as watermark removal, also gets the attention from the community.
Defocus Blur Detection via Depth Distillation
In detail, we learn the defocus blur from ground truth and the depth distilled from a well-trained depth estimation network at the same time.
Towards Ghost-free Shadow Removal via Dual Hierarchical Aggregation Network and Shadow Matting GAN
With the help of novel masks or scenes, we enhance the current datasets using synthesized shadow images.
Ranked #2 on
Shadow Removal
on ISTD
Improving the Harmony of the Composite Image by Spatial-Separated Attention Module
Thus, we address the problem of Image Harmonization: Given a spliced image and the mask of the spliced region, we try to harmonize the "style" of the pasted region with the background (non-spliced region).
Ranked #4 on
Image Harmonization
on HAdobe5k(1024$\times$1024)
Depth Assisted Full Resolution Network for Single Image-based View Synthesis
In this paper, we focus on a more challenging and ill-posed problem that is to synthesize novel viewpoints from one single input image.
