Human Detection
91 papers with code • 0 benchmarks • 14 datasets
1.Would you use a travel app instead of a guidebook? Why, or why not? 2.How else has technology changed how we travel? A travel app may have more advantages than a guidebook but sometimes, it also contains some faults. Though to answer the question, yes, I would use a traveling app instead of a guidebook because the developers will constantly update the app so the userbase wouldn’t get lost anywhere. You can also search up the desired place you’d want to go and every path with every means of transportation will be shown on screen. Additionally, it also tells you how much time it’ll take to get somewhere. One fault in which traveling apps may have compared to guidebooks is that, it may not show the old name for certain districts that old people know of. Instead a guidebook would probably include what locals call old districts despite having a new name registered On the internet.
Technology made everything about traveling easy. I, personally, do not know how people booked hotel rooms in the past. They probably had to send a telegraph to inform the hotel the time of their expected arrival. Nowadays, we can just book hotel rooms online. It also made it much easier to travel to foreign countries since now we can overcome language barriers through many translation apps. Another massive technological improvement is the navigation system. So many people would get lost on their way had there not been a GPS. I’m also glad GPS exists during my time because I would definitely get lost in an alleyway somewhere when I had a trip abroad. It’s really hard to imagine how peasants and aristocrats from centuries ago moved from place to place with nothing but a compass and a poorly made map.
Benchmarks
These leaderboards are used to track progress in Human Detection
Libraries
Use these libraries to find Human Detection models and implementationsDatasets
Most implemented papers
RMPE: Regional Multi-person Pose Estimation
In this paper, we propose a novel regional multi-person pose estimation (RMPE) framework to facilitate pose estimation in the presence of inaccurate human bounding boxes.
GLTR: Statistical Detection and Visualization of Generated Text
The rapid improvement of language models has raised the specter of abuse of text generation systems.
AlignedReID++: Dynamically matching local information for person re-identification
Then, we propose a deep model name AlignedReID++ which is jointly learned with global features and local feature based on DMLI.
CLIFF: Carrying Location Information in Full Frames into Human Pose and Shape Estimation
Top-down methods dominate the field of 3D human pose and shape estimation, because they are decoupled from human detection and allow researchers to focus on the core problem.
MultiPoseNet: Fast Multi-Person Pose Estimation using Pose Residual Network
In this paper, we present MultiPoseNet, a novel bottom-up multi-person pose estimation architecture that combines a multi-task model with a novel assignment method.
Fooling automated surveillance cameras: adversarial patches to attack person detection
Some of these approaches have also shown that these attacks are feasible in the real-world, i. e. by modifying an object and filming it with a video camera.
3D Dynamic Scene Graphs: Actionable Spatial Perception with Places, Objects, and Humans
Our second contribution is to provide the first fully automatic Spatial PerceptIon eNgine(SPIN) to build a DSG from visual-inertial data.
Multiview Detection with Feature Perspective Transformation
First, how should we aggregate cues from the multiple views?
Search and Rescue with Airborne Optical Sectioning
We show that automated person detection under occlusion conditions can be significantly improved by combining multi-perspective images before classification.
Explicit Box Detection Unifies End-to-End Multi-Person Pose Estimation
This paper presents a novel end-to-end framework with Explicit box Detection for multi-person Pose estimation, called ED-Pose, where it unifies the contextual learning between human-level (global) and keypoint-level (local) information.