Search Results for author:
Found 11 papers, 4 papers with code
READ: Reciprocal Attention Discriminator for Image-to-Video Re-Identification
Person re-identification (re-ID) is the problem of visually identifying a person given a database of identities.
Image-To-Video Person Re-Identification
Video-Based Person Re-Identification
Masked Autoencoder for Unsupervised Video Summarization
Summarizing a video requires a diverse understanding of the video, ranging from recognizing scenes to evaluating how much each frame is essential enough to be selected as a summary.
Decomposed Cross-modal Distillation for RGB-based Temporal Action Detection
Temporal action detection aims to predict the time intervals and the classes of action instances in the video.
You Only Train Once: Multi-Identity Free-Viewpoint Neural Human Rendering from Monocular Videos
In this paper, we tackle this problem by proposing a set of learnable identity codes to expand the capability of the framework for multi-identity free-viewpoint rendering, and an effective pose-conditioned code query mechanism to finely model the pose-dependent non-rigid motions.
SEFD: Learning to Distill Complex Pose and Occlusion
This paper addresses the problem of three-dimensional (3D) human mesh estimation in complex poses and occluded situations.
Ranked #1 on
2D Human Pose Estimation
on OCHuman
MEEV: Body Mesh Estimation On Egocentric Video
This technical report introduces our solution, MEEV, proposed to the EgoBody Challenge at ECCV 2022.
Ranked #1 on
3D human pose and shape estimation
on EgoBody
(using extra training data)
Exploring Temporally Dynamic Data Augmentation for Video Recognition
The magnitude of augmentation operations on each frame is changed by an effective mechanism, Fourier Sampling that parameterizes diverse, smooth, and realistic temporal variations.
Out of Sight, Out of Mind: A Source-View-Wise Feature Aggregation for Multi-View Image-Based Rendering
Finally, for each element in the feature set, the aggregation features are extracted by calculating the weighted means and variances, where the weights are derived from the similarity distributions.
Self-Supervised Depth Estimation with Isometric-Self-Sample-Based Learning
Most previous methods have alleviated this issue by removing the dynamic regions in the photometric loss formulation based on the masks estimated from another module, making it difficult to fully utilize the training images.
Detection Recovery in Online Multi-Object Tracking with Sparse Graph Tracker
The strong edge features allow SGT to track targets with tracking candidates selected by top-K scored detections with large K. As a result, even low-scored detections can be tracked, and the missed detections are also recovered.
Ranked #2 on
Multi-Object Tracking
on HiEve
Frequency Selective Augmentation for Video Representation Learning
FreqAug stochastically removes specific frequency components from the video so that learned representation captures essential features more from the remaining information for various downstream tasks.
