Search Results for author:
Found 15 papers, 10 papers with code
Scene Text Detection with Supervised Pyramid Context Network
We propose a supervised pyramid context network (SPCNET) to precisely locate text regions while suppressing false positives.
Ranked #2 on
Scene Text Detection
on ICDAR 2013
Learning to Answer Questions in Dynamic Audio-Visual Scenarios
In this paper, we focus on the Audio-Visual Question Answering (AVQA) task, which aims to answer questions regarding different visual objects, sounds, and their associations in videos.
Ranked #5 on
Audio-visual Question Answering
on MUSIC-AVQA
Self-supervised Audiovisual Representation Learning for Remote Sensing Data
By fine-tuning the models on a number of commonly used remote sensing datasets, we show that our approach outperforms existing pre-training strategies for remote sensing imagery.
Ranked #2 on
Cross-Modal Retrieval
on SoundingEarth
Multi-Scale Attention for Audio Question Answering
Audio question answering (AQA), acting as a widely used proxy task to explore scene understanding, has got more attention.
I Know What You Do Not Know: Knowledge Graph Embedding via Co-distillation Learning
To this end, we propose CoLE, a Co-distillation Learning method for KG Embedding that exploits the complementarity of graph structures and text information.
Rule-Guided Graph Neural Networks for Recommender Systems
However, existing work incorporated with KGs cannot capture the explicit long-range semantics between users and items meanwhile consider various connectivity between items.
Progressive Spatio-temporal Perception for Audio-Visual Question Answering
Such naturally multi-modal videos are composed of rich and complex dynamic audio-visual components, where most of which could be unrelated to the given questions, or even play as interference in answering the content of interest.
Ranked #2 on
Audio-Visual Question Answering (AVQA)
on AVQA
Audio-visual Question Answering
Audio-Visual Question Answering (AVQA)
+2
EventEA: Benchmarking Entity Alignment for Event-centric Knowledge Graphs
Towards a critical evaluation of embedding-based entity alignment methods, we construct a new dataset with heterogeneous relations and attributes based on event-centric KGs.
MECPformer: Multi-estimations Complementary Patch with CNN-Transformers for Weakly Supervised Semantic Segmentation
Given a class, the initial seeds generated based on the transformer may invade regions belonging to other classes.
Weakly supervised Semantic Segmentation
Weakly-Supervised Semantic Segmentation
Prompting Segmentation with Sound Is Generalizable Audio-Visual Source Localizer
Never having seen an object and heard its sound simultaneously, can the model still accurately localize its visual position from the input audio?
Real-world plant species identification based on deep convolutional neural networks and visual attention
We propose a novel framework and an effective data augmentation method for deep learning in this paper.
Deep Inception Generative Network for Cognitive Image Inpainting
Recent advances in deep learning have shown exciting promise in filling large holes and lead to another orientation for image inpainting.
WegFormer: Transformers for Weakly Supervised Semantic Segmentation
Although convolutional neural networks (CNNs) have achieved remarkable progress in weakly supervised semantic segmentation (WSSS), the effective receptive field of CNN is insufficient to capture global context information, leading to sub-optimal results.
Heterogeneous Federated Knowledge Graph Embedding Learning and Unlearning
To cope with the drift between local optimization and global convergence caused by data heterogeneity, we propose mutual knowledge distillation to transfer local knowledge to global, and absorb global knowledge back.
CM-PIE: Cross-modal perception for interactive-enhanced audio-visual video parsing
Audio-visual video parsing is the task of categorizing a video at the segment level with weak labels, and predicting them as audible or visible events.
