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Found 14 papers, 5 papers with code
Tabletop Transparent Scene Reconstruction via Epipolar-Guided Optical Flow with Monocular Depth Completion Prior
Reconstructing transparent objects using affordable RGB-D cameras is a persistent challenge in robotic perception due to inconsistent appearances across views in the RGB domain and inaccurate depth readings in each single-view.
TransNet: Transparent Object Manipulation Through Category-Level Pose Estimation
TransNet is evaluated in terms of pose estimation accuracy on a large-scale transparent object dataset and compared to a state-of-the-art category-level pose estimation approach.
An Operational Perspective to Fairness Interventions: Where and How to Intervene
We demonstrate our framework with a case study on predictive parity.
Pair DETR: Contrastive Learning Speeds Up DETR Training
In this approach, we detect an object bounding box as a pair of keypoints, the top-left corner and the center, using two decoders.
TransNet: Category-Level Transparent Object Pose Estimation
TransNet is evaluated in terms of pose estimation accuracy on a recent, large-scale transparent object dataset and compared to a state-of-the-art category-level pose estimation approach.
TE2Rules: Explaining Tree Ensembles using Rules
Tree Ensemble (TE) models, such as Gradient Boosted Trees, often achieve optimal performance on tabular datasets, yet their lack of transparency poses challenges for comprehending their decision logic.
VLMbench: A Compositional Benchmark for Vision-and-Language Manipulation
We hope the new simulator and benchmark will facilitate future research on language-guided robotic manipulation.
ClearPose: Large-scale Transparent Object Dataset and Benchmark
Transparent objects are ubiquitous in household settings and pose distinct challenges for visual sensing and perception systems.
ProgressLabeller: Visual Data Stream Annotation for Training Object-Centric 3D Perception
We demonstrate the effectiveness of ProgressLabeller by rapidly create a dataset of over 1M samples with which we fine-tune a state-of-the-art pose estimation network in order to markedly improve the downstream robotic grasp success rates.
PatchTrack: Multiple Object Tracking Using Frame Patches
In this paper, we present PatchTrack, a Transformer-based joint-detection-and-tracking system that predicts tracks using patches of the current frame of interest.
Manipulation-Oriented Object Perception in Clutter through Affordance Coordinate Frames
In this work, we combine the notions of affordance and category-level pose, and introduce the Affordance Coordinate Frame (ACF).
LIT: Light-field Inference of Transparency for Refractive Object Localization
With respect to this ProLIT dataset, we demonstrate that LIT can outperform both state-of-the-art end-to-end pose estimation methods and a generative pose estimator on transparent objects.
DigiVoice: Voice Biomarker Featurization and Analysis Pipeline
Simultaneously, voice has shown potential for analysis in precision medicine as a biomarker for screening illnesses.
GRIP: Generative Robust Inference and Perception for Semantic Robot Manipulation in Adversarial Environments
In this work, we propose Generative Robust Inference and Perception (GRIP) as a two-stage object detection and pose estimation system that aims to combine relative strengths of discriminative CNNs and generative inference methods to achieve robust estimation.
