Results 1 to 10 of about 3,421,417 (362)
Unsupervised Learning of Depth and Ego-Motion from Video [PDF]
Computer Vision and Pattern Recognition, 2017 We present an unsupervised learning framework for the task of monocular depth and camera motion estimation from unstructured video sequences. In common with recent work [10, 14, 16], we use an end-to-end learning approach with view synthesis as the ...
Tinghui Zhou +3 more
semanticscholar +1 more source
SadTalker: Learning Realistic 3D Motion Coefficients for Stylized Audio-Driven Single Image Talking Face Animation [PDF]
Computer Vision and Pattern Recognition, 2022 Generating talking head videos through a face image and a piece of speech audio still contains many challenges. i.e., unnatural head movement, distorted expression, and identity modification.
Wenxuan Zhang +7 more
semanticscholar +1 more source
Motion-X: A Large-scale 3D Expressive Whole-body Human Motion Dataset [PDF]
Neural Information Processing Systems, 2023 In this paper, we present Motion-X, a large-scale 3D expressive whole-body motion dataset. Existing motion datasets predominantly contain body-only poses, lacking facial expressions, hand gestures, and fine-grained pose descriptions.
Jing-de Lin +6 more
semanticscholar +1 more source
Guided Motion Diffusion for Controllable Human Motion Synthesis [PDF]
IEEE International Conference on Computer Vision, 2023 Denoising diffusion models have shown great promise in human motion synthesis conditioned on natural language descriptions. However, integrating spatial constraints, such as pre-defined motion trajectories and obstacles, remains a challenge despite being
Korrawe Karunratanakul +3 more
semanticscholar +1 more source
Motion Transformer with Global Intention Localization and Local Movement Refinement [PDF]
Neural Information Processing Systems, 2022 Predicting multimodal future behavior of traffic participants is essential for robotic vehicles to make safe decisions. Existing works explore to directly predict future trajectories based on latent features or utilize dense goal candidates to identify ...
Shaoshuai Shi +3 more
semanticscholar +1 more source
Sampling-based algorithms for optimal motion planning [PDF]
Int. J. Robotics Res., 2011 During the last decade, sampling-based path planning algorithms, such as probabilistic roadmaps (PRM) and rapidly exploring random trees (RRT), have been shown to work well in practice and possess theoretical guarantees such as probabilistic completeness.
S. Karaman, Emilio Frazzoli
semanticscholar +1 more source
MotionCLIP: Exposing Human Motion Generation to CLIP Space [PDF]
European Conference on Computer Vision, 2022 We introduce MotionCLIP, a 3D human motion auto-encoder featuring a latent embedding that is disentangled, well behaved, and supports highly semantic textual descriptions.
Guy Tevet +4 more
semanticscholar +1 more source
Hand in Motion Reveals Mind in Motion [PDF]
Frontiers in Psychology, 2011 Recently, researchers have measured hand movements en route to choices on a screen to understand the dynamics of a broad range of psychological processes. We review this growing body of research and explain how manual action exposes the real-time unfolding of underlying cognitive processing.
Freeman, Jonathan B. +2 more
openaire +3 more sources
Molecular Microbiology, 2006 SummaryMost Apicomplexan are obligate intracellular parasites and at different steps of their life cycle they invade host cells. The invasive forms are generally called zoites and the majority of them largely depend on a unique form of gliding motility to invade cells.
openaire +2 more sources
AMASS: Archive of Motion Capture As Surface Shapes [PDF]
IEEE International Conference on Computer Vision, 2019 Large datasets are the cornerstone of recent advances in computer vision using deep learning. In contrast, existing human motion capture (mocap) datasets are small and the motions limited, hampering progress on learning models of human motion.
Naureen Mahmood +4 more
semanticscholar +1 more source