Search Results for author:
Found 17 papers, 5 papers with code
Clustering Driven Deep Autoencoder for Video Anomaly Detection
Because of the ambiguous definition of anomaly and the complexity of real data, anomaly detection in videos is one of the most challenging problems in intelligent video surveillance.
Generative Motion Stylization within Canonical Motion Space
Our key insight is to embed motion style into a cross-modality latent space and perceive the cross-structure skeleton topologies, allowing for motion stylization within a canonical motion space.
TapMo: Shape-aware Motion Generation of Skeleton-free Characters
In this work, we present TapMo, a Text-driven Animation Pipeline for synthesizing Motion in a broad spectrum of skeleton-free 3D characters.
PHRIT: Parametric Hand Representation with Implicit Template
We propose PHRIT, a novel approach for parametric hand mesh modeling with an implicit template that combines the advantages of both parametric meshes and implicit representations.
Skinned Motion Retargeting with Residual Perception of Motion Semantics & Geometry
Driven by our explored distance-based losses that explicitly model the motion semantics and geometry, these two modules can learn residual motion modifications on the source motion to generate plausible retargeted motion in a single inference without post-processing.
Distilling Inter-Class Distance for Semantic Segmentation
Knowledge distillation is widely adopted in semantic segmentation to reduce the computation cost. The previous knowledge distillation methods for semantic segmentation focus on pixel-wise feature alignment and intra-class feature variation distillation, neglecting to transfer the knowledge of the inter-class distance in the feature space, which is important for semantic segmentation.
Optical Flow for Video Super-Resolution: A Survey
Video super-resolution is currently one of the most active research topics in computer vision as it plays an important role in many visual applications.
MixSTE: Seq2seq Mixed Spatio-Temporal Encoder for 3D Human Pose Estimation in Video
Recent transformer-based solutions have been introduced to estimate 3D human pose from 2D keypoint sequence by considering body joints among all frames globally to learn spatio-temporal correlation.
Ranked #6 on
Monocular 3D Human Pose Estimation
on Human3.6M
Motion-driven Visual Tempo Learning for Video-based Action Recognition
Action visual tempo characterizes the dynamics and the temporal scale of an action, which is helpful to distinguish human actions that share high similarities in visual dynamics and appearance.
Ranked #14 on
Action Recognition
on Something-Something V1
Joint-bone Fusion Graph Convolutional Network for Semi-supervised Skeleton Action Recognition
In recent years, graph convolutional networks (GCNs) play an increasingly critical role in skeleton-based human action recognition.
Consistent 3D Hand Reconstruction in Video via self-supervised Learning
We present a method for reconstructing accurate and consistent 3D hands from a monocular video.
Model-based 3D Hand Reconstruction via Self-Supervised Learning
For the first time, we demonstrate the feasibility of training an accurate 3D hand reconstruction network without relying on manual annotations.
Multi-Attribute Enhancement Network for Person Search
Visual character attributes play a key role in retrieving the query person, which has been explored in Re-ID but has been ignored in Person Search.
Real-time Spatio-temporal Action Localization via Learning Motion Representation
In this paper, we exploit better ways to use motion information in a unified end-to-end trainable network architecture.
Joint Hand-object 3D Reconstruction from a Single Image with Cross-branch Feature Fusion
In this work, we propose to consider hand and object jointly in feature space and explore the reciprocity of the two branches.
Actor-Action Semantic Segmentation with Region Masks
One major challenge for this task is that when an actor performs an action, different body parts of the actor provide different types of cues for the action category and may receive inconsistent action labeling when they are labeled independently.
Salience Guided Depth Calibration for Perceptually Optimized Compressive Light Field 3D Display
Multi-layer light field displays are a type of computational three-dimensional (3D) display which has recently gained increasing interest for its holographic-like effect and natural compatibility with 2D displays.
