Yu Huang
896
Followers
Personal Information
Unternehmen/Arbeitsplatz
San Francisco Bay Area, CA United States
Beruf
Chief Scientist, Global AI Technical Officer, Autonomous Driving
Branche
Technology / Software / Internet
Webseite
sites.google.com/site/yorkyuhuang/
Info
Hands-on experience in those areas:
*Computer Vision, AR*
*Machine (Deep) Learning, Data Mining*
*Cloud computing and distributed deep learning*
*Computational Photography, VR*
*Image/Video Processing*
*Autonomous Driving & ADAS *
Tags
deep learning
cnn
tracking
prediction
rnn
autonomous driving
detection
intention
segmentation
gan
reinforcement learning
modularity
trajectory
camera
driving behavior
aggressive
courteous
abstraction
primitive
transfer learning
database
end-to-end
lidar
depth
selfish
pose estimation
lstm
stereo
unsupervised
regression
pose
behavior
fusion
classification
imitation learning.
gnn
transform
bev
obstacle.
social
imitation learning
crowd
zebra crossing
inter-city
preference
pedestrian
supervised
depth fusion
slam
data augmentation
monocular
vio
vo
projection
mapping
rpn
keypoints
completion
adas
inpainting
2d-to-3d
calibration
planning
perception
domain adaptation
blending
equirectangular
spherical
distortion
surround view
panorama
omnidirectional
fisheye
point cloud
gan.
reinforcement learning.
registration
multi-task
joint training
bounding box
3d proposal
3d cuboid
fcn
vanishing point
ego lane
lane fitting
lane localization
gru
lane detection
prediction.
rgb-d
multiscale
loss
norm
gradient
mask
encoder-decoder network
sparse
depth sensor
sensor fusion
encoder
decoder
annotation tools for training data
localization
data pipeline
boosting
denoising
rain
snow
fog
dust
weather
self driving
monocular camera
3d object detection
semantic
active learning
constrastive learning
teacher-student
pseudo label
semi-supervised
rcs
frustum pointnets
pointnet
focal loss
coordconv
sar
fpn
doppler
faster rcnn
two stage
one stage
ssd
region proposal
radar
feature
anchoring
rgb
late fusion
early fusion
frontal view
multi-modal
cost volume
yolo3d
second
depthcn
pixor
ipod
hdnet
lmnet
birdnet
rt3d
voxelnet
regnet
simulation
machine learning
embodied ai
nerf
diffusion model
world model
llms
foundation model
cloud
long tailed distribution
data close loop
conntrol
decision making
robotaxi
adverse
outliers
dynamic scenario modeling
scenarios clustering
safety testing
autonomous vehicles
scenario-based
self-supervised learning
model testing and verification
large scale model training platform
data driven models
cloud computing infrastructure and big data proces
cameras
annotation
sensor data
behaviors
simulating
safety
transformer
conditional
interactive
hypotheses
forecasting
dynamics
multi-task learning
interaction
graph
data lake
open source code
behavior planning
trajectory prediction
closed loop data pipeline engine
kodiac robotics
aururo
nuro ike
pony tron
waymo via
tusimple
inceptio
telsa semi
plus.ai
commercial truck
3d objeect detection
monocular image
distance
occupancy
sim-to-real
unprojecting
3d
2d
siamese network
dtection-and-tracking
multiple object tracking
single object tracking
self-supervised
continual learning.
knowledge transfer
uncertainty modeling and estimation
instance
curriculum learning
3-d object detection
uncertainty modeling
open world
multiple head
backbone
dpm
color
interpolation
guided
upsampling
residually connected top-down module
context
semantic segmentation
disparity
pyramid stereo matching network
dispsegnet
segstereo
object detection
cornernet-lite
keypoint triplets
centernet
objects as points
ga-rpn
region proposal by guided anchoring
center and scale prediction
foveabox
fully convolutional one-stage
fcos
feature selective anchor-free
fsaf
extremenet
cornernet
yolo
densebox
unitbox
single view metrology
sfm
pnp
aspect graph
selfish.
route planners
driving models
e2e learning
driving policies
driving path
failure prediction for autonomous driving lidar
conditional affordance learning
conditional imitation learning
vehicle navigation
trajectory features
driver behaviors
traffic constraints
dynamic maneuvers
autonomous planning
autonovi
end-to-end.
traffic
scenario
road network
learning
recognizing
modeling
image enhancement
boundary detection
holistically-nested edge detection
image restoration
deepcontour
image/depth superesolution
dehazenet
image deconvolution
joint image processing
colorization.
image denoising
deepedge
edge aware filters
artifact reduction
denoiser prior
image-based relocalization for slam
low level feature description and matching
structure from motion and scene flow
view synthesis
3-d object modeling
image-based modeling
depth/disparity prediction
parametric model
small motion
descriptor matching
global method
regularization and smoothness constraints
horn schunck
focus of expansion
aperture problem
large displacement field
local method
brightness constancy constraints
total variation
lucas-kanade algorithm
optic flow
essential matrix
fundamental matrix
semi-global matching
dynamic programming
hamming distance
optic flow estimation
single image
disparity refinement
rectification
guided filter
cost aggregation
census transform
belief propagation
sparse coding
graph cut
disparity estimation
passive stereo vision
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