Egocentric Future Localization

By Hyun Soo Park, Jyh-Jing Hwang, Yedong Niu, Jianbo Shi. 2016

132 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

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In Computer Vision and Pattern Recognition

Citations in the corpus

Ego4D: Around the World in 3,000 Hours of Egocentric Video (2021, background): “Previous work considers future localization [113, 120, 174, 230], action anticipation [76, 77, 86, 118, 127, 219], next active object prediction [20, 74], future event prediction [149,167], and future frame prediction [145,146,153,215,218,227].”
Scaling Egocentric Vision: The EPIC-KITCHENS Dataset (2018, background): “predicting future localization [49] or next-active object [50].”
Rolling-Unrolling LSTMs for Action Anticipation from First-Person Video (2020, methodology): “Park et al. [59] proposed a method to predict the future trajectories of the camera wearer from egocentric video.”
Who Let the Dogs Out? Modeling Dog Behavior from Visual Data (2018, background): “[26] predict plausible future trajectories of ego-motion in ego-centric stereo images.”
You2Me: Inferring Body Pose in Egocentric Video via First and Second Person Interactions (2019, background): “Egocentric video Recent egocentric vision work focuses primarily on recognizing objects [14], activities [44, 16, 39, 56, 46, 37, 52, 51, 68], visible hand and arm pose [7, 31, 32, 49, 48], eye gaze [33], or anticipating future camera trajectories [41, 9].”
What Would You Expect? Anticipating Egocentric Actions With Rolling-Unrolling LSTMs and Modality Attention (2019, background): “Anticipation in First Person Vision Past works on anticipation from egocentric visual data have investigated different problems and considered different evaluation frameworks [5, 10, 17, 42, 45, 47, 50, 53, 65, 68].”
IntentNet: Learning to Predict Intention from Raw Sensor Data (2018, background): “[23] created an EgoRetinal map to predict plausible future ego-motion trajectories in egocentric stereo images.”
Predicting the Future from First Person (Egocentric) Vision: A Survey (2021, methodology): “The authors of [2] built on EgoRetinal map [141] and performed geometrical modelling to obtain task-speciﬁc features for trajectory prediction.”
Future Person Localization in First-Person Videos (2017, methodology): “• ConstVel: Inspired by the baseline used in [26], this method assumes that target people moved straight at a constant speed.”
The EPIC-KITCHENS Dataset: Collection, Challenges and Baselines (2020, background): “Previous works have investigated different anticipation tasks from an egocentric perspective, including predicting future localisation [62], next-active objects [63] or forecasting actions [64].”
First Person Action-Object Detection with EgoNet (2016, methodology): “cular, egocentric spatial representations [16,21] have demonstrated stronger predictive power than that of a third person for activity recognition [16,17], gaze movement [19,22] and future ego-motion [23]. Such representations were used for various personalized [6,24,25], and social [26,27] interact”
Joint Hand Motion and Interaction Hotspots Prediction from Egocentric Videos (2022, background): “Given that the first-person vision could better capture people’s intention and interactions, as well as its applicability to AR and robotics [39,43,68], estimating human motions in egocentric videos [49,64,88] worth more attention.”
r2p2: A ReparameteRized Pushforward Policy for Diverse, Precise Generative Path Forecasting (2018, background): “Deterministic vehicle predictions are produced in [18], and deterministic pedestrian trajectories are produced in [3,30,34].”
Next-active-object prediction from egocentric videos (2017, methodology): “[39] presented methods to predict future human trajectories from egocentric images.”
Ego-Pose Estimation and Forecasting As Real-Time PD Control (2019, background): “Plenty of work has investigated third-person [61, 31, 3, 21, 1, 43, 65] and firstperson [51] trajectory forecasting, but this line of work only forecasts a person’s future positions instead of poses.”
Forecasting Interactive Dynamics of Pedestrians with Fictitious Play (2016, background): “There has been growing interest in developing computational models of human activities that can extrapolate unseen information and predict future unobserved activities [34, 38, 22, 33, 18, 42, 40, 37, 15, 14, 16, 17, 35, 9, 49, 43, 36, 32].”
DESIRE: Distant Future Prediction in Dynamic Scenes with Interacting Agents (2017, methodology): “A method for future localization from egocentric perspective is also addressed successfully in [30].”