Phu B.

Key Skills

Software

CVAT

Top Subject Matter

3D vehicle analysis using 2D imagery

Face analysis and semantic region annotation

3D vehicle perception (LIDAR/point clouds)

Top Data Types

Image

3D Sensor

Top Task Types

Bounding Box

Polygon

Cuboid

Segmentation

Classification

Freelancer Overview

Lead image annotation (BBox 2D). Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include CVAT. AI-training focus includes data types such as Image and 3D Sensor and labeling workflows including Bounding Box, Polygon, and Cuboid.

Labeling Experience

Semantic segmentation and 3D semantic labeling

CVAT3D SensorSegmentation

Performed segmentation-style labeling for semantic analysis in both 3D and related modalities. Produced detailed region-level annotations to support model training and evaluation. Focused on consistent labeling quality for downstream semantic tasks. • Labeled segmentation regions for 3D semantic understanding • Supported semantic dataset preparation • Performed label QA/QC to reduce inconsistencies • Prepared outputs for training workflows

Present

3D labeling for vehicle analysis (LIDAR/point clouds)

CVAT3D SensorCuboid

Contributed to 3D vehicle analysis labeling using 3D bounding representations such as cuboids. Labeled spatial objects derived from 3D sources to support perception pipelines. Worked on 3D semantic region understanding using LIDAR and point cloud inputs. • Annotated 3D cuboids for vehicles/objects • Labeled using LIDAR point clouds • Supported semantic segmentation labeling for 3D • Assisted QA/QC to improve dataset reliability

Present

Polygon labeling for 2D face/semantic analysis

CVATImagePolygon

Performed polygon-based annotation for face-related analysis and other 2D object regions. Created 2D polygon labels to capture object boundaries more precisely than bounding boxes. Ensured labeled quality to support semantic/segmentation-oriented processing. • Annotated 2D polygon regions for face/surfaces • Labeled polygon boundaries with guideline compliance • Contributed to semantic region definition • Supported QA/QC checks for label consistency

Present

Lead image annotation (BBox 2D)

CVATImageBounding Box

Led image annotation for a 2D/3D vehicle analysis project using bounding boxes. Produced labeled datasets supporting object detection-style workflows across 2D modalities. Coordinated labeling outputs to align with downstream evaluation and QA/QC needs. • Labeled BBox 2D for vehicle and relevant objects • Applied consistent annotation guidelines • Supported dataset refinement through QA/QC • Prepared labels for model training pipelines

Present

Computer Vision Project Lead - N/A

CVATImageBounding BoxPolygon

You led an image analysis and segmentation project focused on 2D and 3D understanding. Your responsibilities included planning labeling workflows, defining annotation quality checks, and supporting data preparation for downstream perception tasks. You worked with bounding boxes, polygons, segmentation, and 3D representations such as cuboids and point clouds using Python skills. • Led 2D and 3D analysis deliverables for a vehicle and object understanding system. • Performed Data QA/QC to improve accuracy and consistency of polygon, BBox, and segmentation outputs. • Supported 3D perception inputs including LIDAR point clouds and cuboid-based representations. • Used Python (basic) and practical communication to coordinate labeling/analysis activities.

2020 - 2021

Show more

Education

Work History