
CIRCLE, a dataset containing 10 hours of full-body reach-ing motion from 5 subjects across nine scenes, paired with ego-centric information of the environment represented in various forms, such as RGBD videos. We use this dataset to train a model that generates human motion conditioned on scene information. Leveraging our dataset, the model
CIRCLE: Capture in Rich Contextual Environments - GitHub Pages
We introduce CIRCLE, a dataset of 3D whole body reaching motion and corresponding first person RGDB videos within a fully furnished virtual home. Synthesizing 3D human motion in a contextual, ecological environment is important for simulating realistic …
CVPR 2023 Open Access Repository
We present CIRCLE, a dataset containing 10 hours of full-body reaching motion from 5 subjects across nine scenes, paired with ego-centric information of the environment represented in various forms, such as RGBD videos. We use this dataset to train a model that generates human motion conditioned on scene information.
[2303.17912] CIRCLE: Capture In Rich Contextual Environments
2023年3月31日 · We present CIRCLE, a dataset containing 10 hours of full-body reaching motion from 5 subjects across nine scenes, paired with ego-centric information of the environment represented in various forms, such as RGBD videos. We use this dataset to train a model that generates human motion conditioned on scene information.
Circle Loss: 一个基于对优化的统一视角-CVPR2020 - 知乎
Circle loss对基于类标签和基于对的标签都有一个统一的公式。 一个统一的视角 深度特征学习目的是最大化类内相似性 s_p ,同时最小化类间相似性。
CVPR Poster CIRCLE: Capture in Rich Contextual Environments
We present CIRCLE, a dataset containing 10 hours of full-body reaching motion from 5 subjects across nine scenes, paired with ego-centric information of the environment represented in various forms, such as RGBD videos. We use this dataset to train a model that generates human motion conditioned on scene information.
Inspired by marine animals that localize the positions of their com-panions underwater through echoes, we build a new angle-based trainable social interaction representation, named SocialCircle, for continuously reflecting the context of so-cial interactions at different angular orientations relative to the target agent.
CIRCLE: Capture In Rich Contextual Environments
2023年3月31日 · This work presents CIRCLE, a dataset containing 10 hours of full-body reaching motion from 5 subjects across nine scenes, paired with ego-centric information of the environment represented in various forms, such as RGBD videos, to train a model that generates human motion conditioned on scene information.
CVPR Poster ConText-CIR: Learning from Concepts in Text for …
Composed image retrieval (CIR) is the task of retrieving a target image specified by a query image and a relative text that describes a semantic modification to the query image. Existing methods in CIR struggle to accurately represent the image and the text modification, resulting in subpar performance.
CIRCLE: Capture In Rich Contextual Environments - Papers With …
We present CIRCLE, a dataset containing 10 hours of full-body reaching motion from 5 subjects across nine scenes, paired with ego-centric information of the environment represented in various forms, such as RGBD videos. We use this dataset to train a model that generates human motion conditioned on scene information.