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Found 8 papers, 2 papers with code
HMD-NeMo: Online 3D Avatar Motion Generation From Sparse Observations
Generating both plausible and accurate full body avatar motion is the key to the quality of immersive experiences in mixed reality scenarios.
Effective Self-supervised Pre-training on Low-compute Networks without Distillation
This hints at view sampling being one of the performance bottlenecks for SSL on low-capacity networks.
iBoot: Image-bootstrapped Self-Supervised Video Representation Learning
Video self-supervised learning (SSL) suffers from added challenges: video datasets are typically not as large as image datasets, compute is an order of magnitude larger, and the amount of spurious patterns the optimizer has to sieve through is multiplied several fold.
JRDB-Act: A Large-scale Dataset for Spatio-temporal Action, Social Group and Activity Detection
However, learning to recognise human actions and their social interactions in an unconstrained real-world environment comprising numerous people, with potentially highly unbalanced and long-tailed distributed action labels from a stream of sensory data captured from a mobile robot platform remains a significant challenge, not least owing to the lack of a reflective large-scale dataset.
Probabilistic Tracklet Scoring and Inpainting for Multiple Object Tracking
Despite the recent advances in multiple object tracking (MOT), achieved by joint detection and tracking, dealing with long occlusions remains a challenge.
Uncertainty Inspired RGB-D Saliency Detection
Our framework includes two main models: 1) a generator model, which maps the input image and latent variable to stochastic saliency prediction, and 2) an inference model, which gradually updates the latent variable by sampling it from the true or approximate posterior distribution.
Ranked #1 on
RGB-D Salient Object Detection
on LFSD
RGB-D Salient Object Detection
RGB Salient Object Detection
+1
Joint Learning of Social Groups, Individuals Action and Sub-group Activities in Videos
In this paper, we solve the problem of simultaneously grouping people by their social interactions, predicting their individual actions and the social activity of each social group, which we call the social task.
ArTIST: Autoregressive Trajectory Inpainting and Scoring for Tracking
One of the core components in online multiple object tracking (MOT) frameworks is associating new detections with existing tracklets, typically done via a scoring function.
