Search Results for author:
Found 13 papers, 6 papers with code
Learning Point-wise Abstaining Penalty for Point Cloud Anomaly Detection
We demonstrate that learning different abstaining penalties, apart from point-wise penalty, for different types of (synthesized) outliers can further improve the performance.
TOPIC: A Parallel Association Paradigm for Multi-Object Tracking under Complex Motions and Diverse Scenes
Existing trackers can be categorized into two association paradigms: single-feature paradigm (based on either motion or appearance feature) and serial paradigm (one feature serves as secondary while the other is primary).
Motion-R3: Fast and Accurate Motion Annotation via Representation-based Representativeness Ranking
In this paper, we follow a data-centric philosophy and propose a novel motion annotation method based on the inherent representativeness of motion data in a given dataset.
Diverse Motion In-betweening with Dual Posture Stitching
In-betweening is a technique for generating transitions given initial and target character states.
A dataset of ant colonies motion trajectories in indoor and outdoor scenes for social cluster behavior study
Motion and interaction of social insects (such as ants) have been studied by many researchers to understand the clustering mechanism.
Swarm behavior tracking based on a deep vision algorithm
In this paper, we propose a detection and tracking framework for multi-ant tracking in the videos by: (1) adopting a two-stage object detection framework using ResNet-50 as backbone and coding the position of regions of interest to locate ants accurately; (2) using the ResNet model to develop the appearance descriptors of ants; (3) constructing long-term appearance sequences and combining them with motion information to achieve online tracking.
Real-World Blind Super-Resolution via Feature Matching with Implicit High-Resolution Priors
Unlike image-space methods, our FeMaSR restores HR images by matching distorted LR image {\it features} to their distortion-free HR counterparts in our pretrained HR priors, and decoding the matched features to obtain realistic HR images.
IGrow: A Smart Agriculture Solution to Autonomous Greenhouse Control
However, the optimal control of autonomous greenhouses is challenging, requiring decision-making based on high-dimensional sensory data, and the scaling of production is limited by the scarcity of labor capable of handling this task.
Evolutionary Gait Transfer of Multi-Legged Robots in Complex Terrains
Given the high dimensions of control space, this problem is particularly challenging for multi-legged robots walking in complex and unknown environments.
Skeleton-bridged Point Completion: From Global Inference to Local Adjustment
Existing works usually estimate the missing shape by decoding a latent feature encoded from the input points.
Total3DUnderstanding: Joint Layout, Object Pose and Mesh Reconstruction for Indoor Scenes from a Single Image
Semantic reconstruction of indoor scenes refers to both scene understanding and object reconstruction.
Ranked #2 on
3D Shape Reconstruction
on Pix3D
Shallow2Deep: Indoor Scene Modeling by Single Image Understanding
Particularly, we design a shallow-to-deep architecture on the basis of convolutional networks for semantic scene understanding and modeling.
Online Bagging for Anytime Transfer Learning
In practical applications, it is often necessary to face online learning problems in which the data samples are achieved sequentially.
