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Found 9 papers, 4 papers with code
Rethink Cross-Modal Fusion in Weakly-Supervised Audio-Visual Video Parsing
Existing works on weakly-supervised audio-visual video parsing adopt hybrid attention network (HAN) as the multi-modal embedding to capture the cross-modal context.
Sketch-based Video Object Segmentation: Benchmark and Analysis
Reference-based video object segmentation is an emerging topic which aims to segment the corresponding target object in each video frame referred by a given reference, such as a language expression or a photo mask.
Generalized Few-Shot Point Cloud Segmentation Via Geometric Words
Existing fully-supervised point cloud segmentation methods suffer in the dynamic testing environment with emerging new classes.
Unsupervised Feature Representation Learning for Domain-generalized Cross-domain Image Retrieval
This limitation motivates us to present the first attempt at domain-generalized unsupervised cross-domain image retrieval (DG-UCDIR) aiming at facilitating image retrieval between any two unseen domains in an unsupervised way.
Motion and Context-Aware Audio-Visual Conditioned Video Prediction
The existing state-of-the-art method for audio-visual conditioned video prediction uses the latent codes of the audio-visual frames from a multimodal stochastic network and a frame encoder to predict the next visual frame.
Feature Representation Learning for Unsupervised Cross-domain Image Retrieval
Current supervised cross-domain image retrieval methods can achieve excellent performance.
Towards Unsupervised Sketch-based Image Retrieval
The practical value of existing supervised sketch-based image retrieval (SBIR) algorithms is largely limited by the requirement for intensive data collection and labeling.
End-To-End Semi-supervised Learning for Differentiable Particle Filters
Recent advances in incorporating neural networks into particle filters provide the desired flexibility to apply particle filters in large-scale real-world applications.
Sketch-a-Classifier: Sketch-based Photo Classifier Generation
Contemporary deep learning techniques have made image recognition a reasonably reliable technology.
