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Found 12 papers, 6 papers with code
Multimodal Variational Auto-encoder based Audio-Visual Segmentation
To achieve this, our ECMVAE factorizes the representations of each modality with a modality-shared representation and a modality-specific representation.
RPEFlow: Multimodal Fusion of RGB-PointCloud-Event for Joint Optical Flow and Scene Flow Estimation
Recently, the RGB images and point clouds fusion methods have been proposed to jointly estimate 2D optical flow and 3D scene flow.
Decomposed Guided Dynamic Filters for Efficient RGB-Guided Depth Completion
The decomposed filters not only maintain the favorable properties of guided dynamic filters as being content-dependent and spatially-variant, but also reduce model parameters and hardware costs, as the learned adaptors are decoupled with the number of feature channels.
Improving Audio-Visual Segmentation with Bidirectional Generation
In this paper, inspired by the human ability to mentally simulate the sound of an object and its visual appearance, we introduce a bidirectional generation framework.
Contrastive Conditional Latent Diffusion for Audio-visual Segmentation
We propose a latent diffusion model with contrastive learning for audio-visual segmentation (AVS) to extensively explore the contribution of audio.
Mutual Information Regularization for Weakly-supervised RGB-D Salient Object Detection
In particular, following the principle of disentangled representation learning, we introduce a mutual information upper bound with a mutual information minimization regularizer to encourage the disentangled representation of each modality for salient object detection.
Joint Appearance and Motion Learning for Efficient Rolling Shutter Correction
Rolling shutter correction (RSC) is becoming increasingly popular for RS cameras that are widely used in commercial and industrial applications.
Learning Dense and Continuous Optical Flow from an Event Camera
In this paper, we propose a novel deep learning-based dense and continuous optical flow estimation framework from a single image with event streams, which facilitates the accurate perception of high-speed motion.
Deep Idempotent Network for Efficient Single Image Blind Deblurring
Single image blind deblurring is highly ill-posed as neither the latent sharp image nor the blur kernel is known.
MUNet: Motion Uncertainty-aware Semi-supervised Video Object Segmentation
The task of semi-supervised video object segmentation (VOS) has been greatly advanced and state-of-the-art performance has been made by dense matching-based methods.
Generative Transformer for Accurate and Reliable Salient Object Detection
For the former, we apply transformer to a deterministic model, and explain that the effective structure modeling and global context modeling abilities lead to its superior performance compared with the CNN based frameworks.
PRAFlow_RVC: Pyramid Recurrent All-Pairs Field Transforms for Optical Flow Estimation in Robust Vision Challenge 2020
Optical flow estimation is an important computer vision task, which aims at estimating the dense correspondences between two frames.
