Optical Flow Estimation
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Latest papers without code
An Internal Learning Approach to Video Inpainting
We propose a novel video inpainting algorithm that simultaneously hallucinates missing appearance and motion (optical flow) information, building upon the recent 'Deep Image Prior' (DIP) that exploits convolutional network architectures to enforce plausible texture in static images.
Temporally Consistent Depth Prediction with Flow-Guided Memory Units
To address this problem, we propose to memorize temporal consistency in the video sequence, and leverage it for the task of depth prediction.
Motion Guided Attention for Video Salient Object Detection
In this paper, we develop a multi-task motion guided video salient object detection network, which learns to accomplish two sub-tasks using two sub-networks, one sub-network for salient object detection in still images and the other for motion saliency detection in optical flow images.
OPTICAL FLOW ESTIMATION SALIENCY DETECTION SALIENT OBJECT DETECTION
Learning Residual Flow as Dynamic Motion from Stereo Videos
Based on rigid projective geometry, the estimated stereo depth is used to guide the camera motion estimation, and the depth and camera motion are used to guide the residual flow estimation.
DEPTH AND CAMERA MOTION MOTION ESTIMATION OPTICAL FLOW ESTIMATION STEREO MATCHING VISUAL ODOMETRY
Visuomotor Understanding for Representation Learning of Driving Scenes
We postulate that success on this task requires the network to learn semantic and geometric knowledge in the ego-centric view.
OPTICAL FLOW ESTIMATION REPRESENTATION LEARNING SCENE UNDERSTANDING SEMANTIC SEGMENTATION
Multimodal Deep Models for Predicting Affective Responses Evoked by Movies
Interestingly, we also observe that the optical flow is more informative than the RGB in videos, and overall, models using audio features are more accurate than those based on video features when making the final prediction of evoked emotions.
Human Following for Wheeled Robot with Monocular Pan-tilt Camera
Human following on mobile robots has witnessed significant advances due to its potentials for real-world applications.
Video Interpolation and Prediction with Unsupervised Landmarks
Prediction and interpolation for long-range video data involves the complex task of modeling motion trajectories for each visible object, occlusions and dis-occlusions, as well as appearance changes due to viewpoint and lighting.
Multiple Object Tracking with Motion and Appearance Cues
Due to better video quality and higher frame rate, the performance of multiple object tracking issues has been greatly improved in recent years.
Small Obstacle Avoidance Based on RGB-D Semantic Segmentation
This paper presents a novel obstacle avoidance system for road robots equipped with RGB-D sensor that captures scenes of its way forward.