Search Results for author:
Found 9 papers, 3 papers with code
Unsupervised Modality-Transferable Video Highlight Detection with Representation Activation Sequence Learning
To achieve unsupervised highlight detection, we investigate the latent representations of the network and propose the representation activation sequence learning (RASL) module with k-point contrastive learning to learn significant representation activations.
RE-SORT: Removing Spurious Correlation in Multilevel Interaction for CTR Prediction
Click-through rate (CTR) prediction is a critical task in recommendation systems, serving as the ultimate filtering step to sort items for a user.
DELTA: Dynamic Embedding Learning with Truncated Conscious Attention for CTR Prediction
To tackle this problem, inspired by the Global Workspace Theory in conscious processing, which posits that only a specific subset of the product features are pertinent while the rest can be noisy and even detrimental to human-click behaviors, we propose a CTR model that enables Dynamic Embedding Learning with Truncated Conscious Attention for CTR prediction, termed DELTA.
Discovering Interpretable Latent Space Directions of GANs Beyond Binary Attributes
In this way, arbitrary attributes can be edited by collecting positive data only, and the proposed method learns a controllable representation enabling manipulation of non-binary attributes like anime styles and facial characteristics.
Deep Music Retrieval for Fine-Grained Videos by Exploiting Cross-Modal-Encoded Voice-Overs
In this paper, we also investigate the widely added voice-overs in short videos and propose a novel framework to retrieve BGM for fine-grained short videos.
Group-Skeleton-Based Human Action Recognition in Complex Events
In this paper, we propose a novel group-skeleton-based human action recognition method in complex events.
Unsupervised Multi-stream Highlight detection for the Game "Honor of Kings"
With the increasing popularity of E-sport live, Highlight Flashback has been a critical functionality of live platforms, which aggregates the overall exciting fighting scenes in a few seconds.
Understanding Video Content: Efficient Hero Detection and Recognition for the Game "Honor of Kings"
In order to understand content and automatically extract labels for videos of the game "Honor of Kings", it is necessary to detect and recognize characters (called "hero") together with their camps in the game video.
News Cover Assessment via Multi-task Learning
We propose an end-to-end multi-task learning network for image clarity assessment and semantic segmentation simultaneously, the results of which can be guided for news cover assessment.
