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Found 17 papers, 5 papers with code
Self-supervised 6-DoF Robot Grasping by Demonstration via Augmented Reality Teleoperation System
Most existing 6-DoF robot grasping solutions depend on strong supervision on grasp pose to ensure satisfactory performance, which could be laborious and impractical when the robot works in some restricted area.
The Lottery Ticket Hypothesis in Denoising: Towards Semantic-Driven Initialization
Text-to-image diffusion models allow users control over the content of generated images.
Angle Range and Identity Similarity Enhanced Gaze and Head Redirection based on Synthetic data
In this paper, we propose a method for improving the angular accuracy and photo-reality of gaze and head redirection in full-face images.
Multimodal Color Recommendation in Vector Graphic Documents
Additionally, it is applicable for another color recommendation task, full palette generation, which generates a complete color palette corresponding to the given text.
Guided Image Synthesis via Initial Image Editing in Diffusion Model
Diffusion models have the ability to generate high quality images by denoising pure Gaussian noise images.
Training-Free Location-Aware Text-to-Image Synthesis
Current large-scale generative models have impressive efficiency in generating high-quality images based on text prompts.
Color Recommendation for Vector Graphic Documents based on Multi-Palette Representation
We train the model and build a color recommendation system on a large-scale dataset of vector graphic documents.
Edge-Level Explanations for Graph Neural Networks by Extending Explainability Methods for Convolutional Neural Networks
Graph Neural Networks (GNNs) are deep learning models that take graph data as inputs, and they are applied to various tasks such as traffic prediction and molecular property prediction.
Predicting Online Video Advertising Effects with Multimodal Deep Learning
With expansion of the video advertising market, research to predict the effects of video advertising is getting more attention.
Pretext-Contrastive Learning: Toward Good Practices in Self-supervised Video Representation Leaning
It is convenient to treat PCL as a standard training strategy and apply it to many other works in self-supervised video feature learning.
Ranked #10 on
Self-supervised Video Retrieval
on UCF101
Self-Play Reinforcement Learning for Fast Image Retargeting
In this study, we address image retargeting, which is a task that adjusts input images to arbitrary sizes.
Self-supervised Video Representation Learning Using Inter-intra Contrastive Framework
With the proposed Inter-Intra Contrastive (IIC) framework, we can train spatio-temporal convolutional networks to learn video representations.
Ranked #10 on
Self-supervised Video Retrieval
on HMDB51
Image Aesthetics Prediction Using Multiple Patches Preserving the Original Aspect Ratio of Contents
The spread of social networking services has created an increasing demand for selecting, editing, and generating impressive images.
Motion Representation Using Residual Frames with 3D CNN
In this paper, we propose a fast but effective way to extract motion features from videos utilizing residual frames as the input data in 3D ConvNets.
DeepSperm: A robust and real-time bull sperm-cell detection in densely populated semen videos
This study proposes an architecture, called DeepSperm, that solves the aforementioned challenges and is more accurate and faster than state-of-the-art architectures.
Rethinking Motion Representation: Residual Frames with 3D ConvNets for Better Action Recognition
Further analysis indicates that better motion features can be extracted using residual frames with 3D ConvNets, and our residual-frame-input path is a good supplement for existing RGB-frame-input models.
Weakly Supervised Video Summarization by Hierarchical Reinforcement Learning
For each subtask, the manager is trained to set a subgoal only by a task-level binary label, which requires much fewer labels than conventional approaches.
Hierarchical Reinforcement Learning
reinforcement-learning
+2
