We propose a novel transformer-based framework that reconstructs two hig...
With the rapid development of deep learning technology in the past decad...
Face rendering using neural radiance fields (NeRF) is a rapidly developi...
Denoising diffusion probabilistic models that were initially proposed fo...
Clothes grasping and unfolding is a core step in robotic-assisted dressi...
Temporal modeling is crucial for multi-frame human pose estimation. Most...
In this paper, we propose a novel 3D graph convolution based pipeline fo...
Despite the recent efforts in accurate 3D annotations in hand and object...
We propose a new transformer model for the task of unsupervised learning...
Estimating the pose and shape of hands and objects under interaction fin...
We propose a novel optimization framework that crops a given image based...
Utilizing vicinal space between the source and target domains is one of ...
Deterministic approaches using iterative optimisation have been historic...
Data-driven deep learning approaches to image registration can be less
a...
Most of the existing literature regarding hyperbolic embedding concentra...
In this paper, we focus on category-level 6D pose and size estimation fr...
Predictor combination aims to improve a (target) predictor of a learning...
3D hand pose estimation based on RGB images has been studied for a long ...
We propose Aggregation with Class-Attentive Diffusion (AggCAD), a novel
...
Recent work in the behavioural sciences has begun to overturn the long-h...
Active Learning for discriminative models has largely been studied with ...
In this paper, we propose a novel real-time 6D object pose estimation
fr...
We propose a self-supervised learning method by predicting the variable
...
This paper proposes a new high dimensional regression method by merging
...
We propose a symmetric graph convolutional autoencoder which produces a
...
We present a new predictor combination algorithm that improves a given t...
We propose a new context-aware correlation filter based tracking framewo...
This paper introduces a cognitive architecture for a humanoid robot to e...
We propose the Margin Adaptation for Generative Adversarial Networks (MA...