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Found 13 papers, 5 papers with code
Human Interaction Learning on 3D Skeleton Point Clouds for Video Violence Recognition
This paper introduces a new method for recognizing violent behavior by learning contextual relationships between related people from human skeleton points.
Ranked #5 on
Activity Recognition
on RWF-2000
Spatial-Semantic Collaborative Cropping for User Generated Content
A large amount of User Generated Content (UGC) is uploaded to the Internet daily and displayed to people world-widely through the client side (e. g., mobile and PC).
DI-Net : Decomposed Implicit Garment Transfer Network for Digital Clothed 3D Human
3D virtual try-on enjoys many potential applications and hence has attracted wide attention.
COMNet: Co-Occurrent Matching for Weakly Supervised Semantic Segmentation
Image-level weakly supervised semantic segmentation is a challenging task that has been deeply studied in recent years.
Semantic-Constraint Matching Transformer for Weakly Supervised Object Localization
Weakly supervised object localization (WSOL) strives to learn to localize objects with only image-level supervision.
Occlusion-Aware Detection and Re-ID Calibrated Network for Multi-Object Tracking
Multi-Object Tracking (MOT) is a crucial computer vision task that aims to predict the bounding boxes and identities of objects simultaneously.
AIoT-Based Drum Transcription Robot using Convolutional Neural Networks
With the development of information technology, robot technology has made great progress in various fields.
Improving Video Violence Recognition with Human Interaction Learning on 3D Skeleton Point Clouds
(ii) Global-SPIL: to better learn and refine the features of the unordered and unstructured skeleton points, Global-SPIL employs the self-attention layer that operates directly on the sampled points, which can help to make the output more permutation-invariant and well-suited for our task.
Dual Progressive Transformations for Weakly Supervised Semantic Segmentation
Weakly supervised semantic segmentation (WSSS), which aims to mine the object regions by merely using class-level labels, is a challenging task in computer vision.
A Unified Transformer Framework for Group-based Segmentation: Co-Segmentation, Co-Saliency Detection and Video Salient Object Detection
Besides, they fail to take full advantage of the cues among inter- and intra-feature within a group of images.
Ranked #1 on
Video Salient Object Detection
on FBMS-59
Context Decoupling Augmentation for Weakly Supervised Semantic Segmentation
Data augmentation is vital for deep learning neural networks.
Self-Supervised 3D Skeleton Action Representation Learning With Motion Consistency and Continuity
Recently, self-supervised learning (SSL) has been proved very effective and it can help boost the performance in learning representations from unlabeled data in the image domain.
MU-GAN: Facial Attribute Editing based on Multi-attention Mechanism
Facial attribute editing has mainly two objectives: 1) translating image from a source domain to a target one, and 2) only changing the facial regions related to a target attribute and preserving the attribute-excluding details.
