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Found 29 papers, 9 papers with code
Hierarchical Masked 3D Diffusion Model for Video Outpainting
Our pipeline benefits from bidirectional learning of the mask modeling and thus can employ a hybrid strategy of infilling and interpolation when generating sparse frames.
Deep Task-specific Bottom Representation Network for Multi-Task Recommendation
In this paper, we focus on the bottom representation learning of MTL in RS and propose the Deep Task-specific Bottom Representation Network (DTRN) to alleviate the negative transfer problem.
TextPainter: Multimodal Text Image Generation with Visual-harmony and Text-comprehension for Poster Design
Specifically, TextPainter takes the global-local background image as a hint of style and guides the text image generation with visual harmony.
AutoPoster: A Highly Automatic and Content-aware Design System for Advertising Poster Generation
Meanwhile, to our knowledge, we propose the first poster generation dataset that includes visual attribute annotations for over 76k posters.
Visual Captioning at Will: Describing Images and Videos Guided by a Few Stylized Sentences
To address these limitations, we explore the problem of Few-Shot Stylized Visual Captioning, which aims to generate captions in any desired style, using only a few examples as guidance during inference, without requiring further training.
Edit As You Wish: Video Description Editing with Multi-grained Commands
In this paper, we propose a novel Video Description Editing (VDEdit) task to automatically revise an existing video description guided by flexible user requests.
Unsupervised Domain Adaption with Pixel-level Discriminator for Image-aware Layout Generation
This paper focuses on using the GAN-based model conditioned on image contents to generate advertising poster graphic layouts, which requires an advertising poster layout dataset with paired product images and graphic layouts.
CF-Font: Content Fusion for Few-shot Font Generation
Content and style disentanglement is an effective way to achieve few-shot font generation.
Video Object of Interest Segmentation
Given a video and a target image of interest, our objective is to simultaneously segment and track all objects in the video that are relevant to the target image.
Motion and Appearance Adaptation for Cross-Domain Motion Transfer
Motion transfer aims to transfer the motion of a driving video to a source image.
Motion Transformer for Unsupervised Image Animation
Image animation aims to animate a source image by using motion learned from a driving video.
Geometry Aligned Variational Transformer for Image-conditioned Layout Generation
First, self-attention mechanism is adopted to model the contextual relationship within layout elements, while cross-attention mechanism is used to fuse the visual information of conditional images.
Attract me to Buy: Advertisement Copywriting Generation with Multimodal Multi-structured Information
Therefore, we present a dataset, E-MMAD (e-commercial multimodal multi-structured advertisement copywriting), which requires, and supports much more detailed information in text generation.
Dual-Level Decoupled Transformer for Video Captioning
As for the latter, \textbf{\textit{"couple"}} means treating the generation of visual semantic and syntax-related words equally.
Composition-aware Graphic Layout GAN for Visual-textual Presentation Designs
Through both quantitative and qualitative evaluations, we demonstrate that the proposed model can synthesize high-quality graphic layouts according to image compositions.
Self-Supervised Text Erasing with Controllable Image Synthesis
The synthetic training images with erasure ground-truth are then fed to train a coarse-to-fine erasing network.
CapOnImage: Context-driven Dense-Captioning on Image
Existing image captioning systems are dedicated to generating narrative captions for images, which are spatially detached from the image in presentation.
Estimation of Reliable Proposal Quality for Temporal Action Detection
For the region perspective, we introduce Region Evaluate Module (REM) which uses a new and efficient sampling method for proposal feature representation containing more contextual information compared with point feature to refine category score and proposal boundary.
Structure-Aware Motion Transfer with Deformable Anchor Model
Specifically, inspired by the known deformable part model (DPM), our DAM introduces two types of anchors or keypoints: i) a number of motion anchors that capture both appearance and motion information from the source image and driving video; ii) a latent root anchor, which is linked to the motion anchors to facilitate better learning of the representations of the object structure information.
Learning Pixel-Level Distinctions for Video Highlight Detection
To this end, we propose to learn pixel-level distinctions to improve the video highlight detection.
Move As You Like: Image Animation in E-Commerce Scenario
Creative image animations are attractive in e-commerce applications, where motion transfer is one of the import ways to generate animations from static images.
Boosting Image Outpainting with Semantic Layout Prediction
Secondly, another GAN model is trained to synthesize real images based on the extended semantic layouts.
Efficient Optimal Selection for Composited Advertising Creatives with Tree Structure
Based on the tree structure, Thompson sampling is adapted with dynamic programming, leading to efficient exploration for potential ad creatives with the largest CTR.
Automated Creative Optimization for E-Commerce Advertising
However, interactions between creative elements may be more complex than the inner product, and the FM-estimated CTR may be of high variance due to limited feedback.
A Hybrid Bandit Model with Visual Priors for Creative Ranking in Display Advertising
Creative plays a great important role in e-commerce for exhibiting products.
Semantic Human Matting
SHM is the first algorithm that learns to jointly fit both semantic information and high quality details with deep networks.
Ranked #4 on
Image Matting
on AIM-500
Image Matters: Visually modeling user behaviors using Advanced Model Server
So we propose to model user preference jointly with user behavior ID features and behavior images.
Product Sparse Coding
In this paper, we study a special case of sparse coding in which the codebook is a Cartesian product of two subcodebooks.
Optimized Product Quantization for Approximate Nearest Neighbor Search
Product quantization is an effective vector quantization approach to compactly encode high-dimensional vectors for fast approximate nearest neighbor (ANN) search.
