b-hakim

ava-dataset

The AVA dataset densely annotates 80 atomic visual actions in 351k movie clips with actions localized in space and time, resulting in 1.65M action labels with multiple labels per human occurring frequently.

C3D-keras

train C3D with keras for action recognition

c3d_on_ucf101

carrot_lettuce_game

This game is for made for first year summer course training in FCIS ASU.

CP-STC

LTE V2X Broadcasting

door_builder_stds

extended_vehicle_percecption

insurance_prediction

multi_action_recognition

video_labeling_tool_for_action_detection

b-hakim/extended_vehicle_percecption

b-hakim/video_labeling_tool_for_action_detection

b-hakim/multi_action_recognition

b-hakim/ava-dataset

The AVA dataset densely annotates 80 atomic visual actions in 351k movie clips with actions localized in space and time, resulting in 1.65M action labels with multiple labels per human occurring frequently.

b-hakim/C3D-keras

train C3D with keras for action recognition

b-hakim/c3d_on_ucf101

b-hakim/carrot_lettuce_game

This game is for made for first year summer course training in FCIS ASU.

b-hakim/CP-STC

LTE V2X Broadcasting

b-hakim/door_builder_stds

b-hakim/insurance_prediction

b-hakim/lcm

Lightweight Communications and Marshalling

b-hakim/MHA-JAM

b-hakim/mitigating_redundant_messages

b-hakim/multi-temporal-resolution-c3d

b-hakim/ns3_tutorials

b-hakim/nuscenes-devkit

The devkit of the nuScenes dataset.

b-hakim/problem_solving

b-hakim/SUMO-Carla-integration

b-hakim/sumo2vision

Simulate perception sensors and object detection based on traffic data generated by Sumo

b-hakim/TrackNPred

This is the code base for our ACM CSCS 2019 paper: "RobustTP: End-to-End Trajectory Prediction for Heterogeneous Road-Agents in Dense Traffic with Noisy Sensor Inputs". This codebase contains implementations for several trajectory prediction methods including Social-GAN and TraPHic.

b-hakim/Trajectory-Transformer

Code for "Transformer Networks for Trajectory Forecasting"

b-hakim/visualize_cnn