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Found 18 papers, 3 papers with code
Agent AI: Surveying the Horizons of Multimodal Interaction
To accelerate research on agent-based multimodal intelligence, we define "Agent AI" as a class of interactive systems that can perceive visual stimuli, language inputs, and other environmentally-grounded data, and can produce meaningful embodied actions.
GPT-4V(ision) for Robotics: Multimodal Task Planning from Human Demonstration
The computation starts by analyzing the videos with GPT-4V to convert environmental and action details into text, followed by a GPT-4-empowered task planner.
Bias in Emotion Recognition with ChatGPT
This technical report explores the ability of ChatGPT in recognizing emotions from text, which can be the basis of various applications like interactive chatbots, data annotation, and mental health analysis.
PoseRN: A 2D pose refinement network for bias-free multi-view 3D human pose estimation
We propose a new 2D pose refinement network that learns to predict the human bias in the estimated 2D pose.
Ranked #67 on
3D Human Pose Estimation
on Human3.6M
Text-driven object affordance for guiding grasp-type recognition in multimodal robot teaching
These findings highlight the significance of object affordance in multimodal robot teaching, regardless of whether real objects are present in the images.
Understanding Action Sequences based on Video Captioning for Learning-from-Observation
We propose a Learning-from-Observation framework that splits and understands a video of a human demonstration with verbal instructions to extract accurate action sequences.
Learning-from-Observation Framework: One-Shot Robot Teaching for Grasp-Manipulation-Release Household Operations
In the context of one-shot robot teaching, the contributions of the paper are: 1) to propose a framework that 1) covers various tasks in grasp-manipulation-release class household operations and 2) mimics human postures during the operations.
Robotics Human-Computer Interaction
Representing a Partially Observed Non-Rigid 3D Human Using Eigen-Texture and Eigen-Deformation
For full-body reconstruction with loose clothes, we propose to use lower dimensional embeddings of texture and deformation referred to as eigen-texturing and eigen-deformation, to reproduce views of even unobserved surfaces.
LiDAR and Camera Calibration using Motion Estimated by Sensor Fusion Odometry
In this paper, we propose a method of targetless and automatic Camera-LiDAR calibration.
Offline and Online calibration of Mobile Robot and SLAM Device for Navigation
In the experiments, we confirm the parameters obtained by two types of offline calibration according to the degree of freedom of robot movement and validate the effectiveness of online correction method by plotting localized position error during robot's intense movement.
Specular Highlight Removal in Facial Images
An important practical feature of the proposed method is that the skin color model is utilized in a way that does not require color calibration of the camera.
Radiometric Calibration From Faces in Images
We present a method for radiometric calibration of cameras from a single image that contains a human face.
Reconstructing Shapes and Appearances of Thin Film Objects Using RGB Images
First, we narrow down candidates of zenith angle by degree of polarization and determine it by the intensity of thin film which increases monotonically along the zenith angle.
Multiview Rectification of Folded Documents
Digitally unwrapping images of paper sheets is crucial for accurate document scanning and text recognition.
Waterdrop Stereo
(2) The imagery inside a water-drop is determined by the water-drop 3D shape and total reflection at the boundary.
Robust 3D Features for Matching between Distorted Range Scans Captured by Moving Systems
Our feature description is designed as two steps: 1) we normalize the detected local regions to canonical shapes for robust matching; 2) we encode each key point with multiple vectors at different Morse function values.
Adherent Raindrop Detection and Removal in Video
First, it detects raindrops based on the motion and the intensity temporal derivatives of the input video.
Beyond Point Clouds: Scene Understanding by Reasoning Geometry and Physics
In this paper, we present an approach for scene understanding by reasoning physical stability of objects from point cloud.
