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Found 30 papers, 11 papers with code
ConViTac: Aligning Visual-Tactile Fusion with Contrastive Representations
In this paper, we propose ConViTac, a visual-tactile representation learning network designed to enhance the alignment of features during fusion using contrastive representations.
Point Cloud-based Grasping for Soft Hand Exoskeleton
Grasping is a fundamental skill for interacting with and manipulating objects in the environment.
CDI3D: Cross-guided Dense-view Interpolation for 3D Reconstruction
However, challenges remain as 2D diffusion models often struggle to produce dense images with strong multi-view consistency, and LRMs tend to amplify these inconsistencies during the 3D reconstruction process.
Adversarial Diffusion Model for Unsupervised Domain-Adaptive Semantic Segmentation
Semantic segmentation requires labour-intensive labelling tasks to obtain the supervision signals, and because of this issue, it is encouraged that using domain adaptation, which transfers information from the existing labelled source domains to unlabelled or weakly labelled target domains, is essential.
Fractal Calibration for long-tailed object detection
FRACAL devises a logit adjustment method that utilises the fractal dimension to estimate how uniformly classes are distributed in image space.
Ranked #10 on
Instance Segmentation
on LVIS v1.0 val
TopoFR: A Closer Look at Topology Alignment on Face Recognition
To address this problem, we propose TopoFR, a novel FR model that leverages a topological structure alignment strategy called PTSA and a hard sample mining strategy named SDE.
ManiSkill3: GPU Parallelized Robotics Simulation and Rendering for Generalizable Embodied AI
We introduce and open source ManiSkill3, the fastest state-visual GPU parallelized robotics simulator with contact-rich physics targeting generalizable manipulation.
STS MICCAI 2023 Challenge: Grand challenge on 2D and 3D semi-supervised tooth segmentation
The Semi-supervised Teeth Segmentation (STS) Challenge, a pioneering event in tooth segmentation, was held as a part of the MICCAI 2023 ToothFairy Workshop on the Alibaba Tianchi platform.
Adaptive Parametric Activation
In this work, we delve deeper in this phenomenon by performing a comprehensive statistical analysis in the classification and intermediate layers of both balanced and imbalanced networks and we empirically show that aligning the activation function with the data distribution, enhances the performance in both balanced and imbalanced tasks.
Ranked #11 on
Long-tail Learning
on Places-LT
PointGrasp: Point Cloud-based Grasping for Tendon-driven Soft Robotic Glove Applications
The proposed pipeline demonstrates an average RMSE of 0. 8 $\pm$ 0. 39 cm for simple and 0. 11 $\pm$ 0. 06 cm for complex geometries.
Multi-class Road Defect Detection and Segmentation using Spatial and Channel-wise Attention for Autonomous Road Repairing
To demonstrate the effectiveness of our framework, we conducted various ablation studies and comparisons with prior methods on a newly collected dataset annotated with nine road defect classes.
Road Surface Defect Detection -- From Image-based to Non-image-based: A Survey
As a result, there has been a growing interest in the literature on the subject, leading to the development of various road surface defect detection methods.
Generating Future Observations to Estimate Grasp Success in Cluttered Environments
End-to-end self-supervised models have been proposed for estimating the success of future candidate grasps and video predictive models for generating future observations.
Inverse Image Frequency for Long-tailed Image Recognition
The long-tailed distribution is a common phenomenon in the real world.
Long-tailed Instance Segmentation using Gumbel Optimized Loss
Major advancements have been made in the field of object detection and segmentation recently.
Ranked #17 on
Instance Segmentation
on LVIS v1.0 val
Fast Composite Optimization and Statistical Recovery in Federated Learning
This paper investigates a class of composite optimization and statistical recovery problems in the FL setting, whose loss function consists of a data-dependent smooth loss and a non-smooth regularizer.
TC-SfM: Robust Track-Community-Based Structure-from-Motion
Specifically, a novel structure is proposed, namely, {\textit{track-community}}, in which each community consists of a group of tracks and represents a local segment in the scene.
Visual-Tactile Multimodality for Following Deformable Linear Objects Using Reinforcement Learning
It will be problematic to use a single sensory input to track the behaviour of such objects: vision can be subjected to occlusions, whereas tactile inputs cannot capture the global information that is useful for the task.
Multimodal perception for dexterous manipulation
Due to the complementary properties between visual and tactile senses, it is desirable for us to combine vision and touch for a synergistic perception and manipulation.
Logic Rules Meet Deep Learning: A Novel Approach for Ship Type Classification
The shipping industry is an important component of the global trade and economy, however in order to ensure law compliance and safety it needs to be monitored.
Representation and Processing of Instantaneous and Durative Temporal Phenomena
In this paper, we propose a new logic based temporal phenomena definition language, specifically tailored for Complex Event Processing, that allows the representation of both instantaneous and durative phenomena and the temporal relations between them.
Vision-Guided Active Tactile Perception for Crack Detection and Reconstruction
In recent years, computer vision techniques have been applied in detecting cracks in concrete structures.
Generation of GelSight Tactile Images for Sim2Real Learning
Preliminary experimental results have shown that the simulated sensor could generate realistic outputs similar to the ones captured by a real GelSight sensor.
Robotics
Spatio-temporal Attention Model for Tactile Texture Recognition
Recently, tactile sensing has attracted great interest in robotics, especially for facilitating exploration of unstructured environments and effective manipulation.
Surface Following using Deep Reinforcement Learning and a GelSightTactile Sensor
Tactile sensors can provide detailed contact in-formation that can facilitate robots to perform dexterous, in-hand manipulation tasks.
Robotics
GarmNet: Improving Global with Local Perception for Robotic Laundry Folding
Developing autonomous assistants to help with domestic tasks is a vital topic in robotics research.
Neural Logic Reinforcement Learning
Deep reinforcement learning (DRL) has achieved significant breakthroughs in various tasks.
ViTac: Feature Sharing between Vision and Tactile Sensing for Cloth Texture Recognition
In this paper, addressing for the first time (to the best of our knowledge) texture recognition from tactile images and vision, we propose a new fusion method named Deep Maximum Covariance Analysis (DMCA) to learn a joint latent space for sharing features through vision and tactile sensing.
Robotic Tactile Perception of Object Properties: A Review
Available tactile sensing technologies are briefly presented before an extensive review on tactile recognition of object properties.
Knock-Knock: Acoustic Object Recognition by using Stacked Denoising Autoencoders
A traditional method using handcrafted features with a shallow classifier was taken as a benchmark and the attained recognition rate was only 58. 22%.
