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Found 19 papers, 2 papers with code
Gradient Obfuscation Checklist Test Gives a False Sense of Security
It has since become a trend to use these five characteristics as a sufficient test, to determine whether or not gradient obfuscation is the main source of robustness.
Spatially Multi-conditional Image Generation
However, multi-conditional image generation is a very challenging problem due to the heterogeneity and the sparsity of the (in practice) available conditioning labels.
Improving the Behaviour of Vision Transformers with Token-consistent Stochastic Layers
We use linear layers with token-consistent stochastic parameters inside the multilayer perceptron blocks, without altering the architecture of the transformer.
Rethinking Global Context in Crowd Counting
This paper investigates the role of global context for crowd counting.
Open-Ended Automatic Programming Through Combinatorial Evolution
We found that reserved keywords of a programming language are suitable for defining the basic code blocks at the beginning of the simulation.
Task Switching Network for Multi-Task Learning
Multiple tasks are performed by switching between them, performing one task at a time.
Unsupervised Monocular Depth Reconstruction of Non-Rigid Scenes
In this work, we present an unsupervised monocular framework for dense depth estimation of dynamic scenes, which jointly reconstructs rigid and non-rigid parts without explicitly modelling the camera motion.
CompositeTasking: Understanding Images by Spatial Composition of Tasks
Learning to perform spatially distributed tasks is motivated by the frequent availability of only sparse labels across tasks, and the desire for a compact multi-tasking network.
Convex Relaxations for Consensus and Non-Minimal Problems in 3D Vision
Notably, we further exploit the POP formulation of non-minimal solver also for the generic consensus maximization problems in 3D vision.
Dual Grid Net: hand mesh vertex regression from single depth maps
In the first stage, the network estimates a dense correspondence field for every pixel on the depth map or image grid to the mesh grid.
What Correspondences Reveal About Unknown Camera and Motion Models?
Problems such as Structure-from-Motion (SfM) and camera self-calibration are tackled under the assumptions of a specific camera projection model and motion type.
Unsupervised Learning of Consensus Maximization for 3D Vision Problems
This model fitting cost is used as a supervisory signal for learning consensus maximization, where the learning process seeks for the largest measurement set that minimizes the proposed model fitting cost.
Mapping, Localization and Path Planning for Image-based Navigation using Visual Features and Map
The problem of localization often arises as part of a navigation process.
Incremental Non-Rigid Structure-from-Motion with Unknown Focal Length
In this paper we present a method for incremental Non-Rigid Structure-from-Motion (NRSfM) with the perspective camera model and the isometric surface prior with unknown focal length.
Model-free Consensus Maximization for Non-Rigid Shapes
In this paper, we formulate the model-free consensus maximization as an Integer Program in a graph using `rules' on measurements.
Dense 3D Regression for Hand Pose Estimation
Specifically, we decompose the pose parameters into a set of per-pixel estimations, i. e., 2D heat maps, 3D heat maps and unit 3D directional vector fields.
Ranked #4 on
Hand Pose Estimation
on MSRA Hands
Automatic Tool Landmark Detection for Stereo Vision in Robot-Assisted Retinal Surgery
In recent works, such interventions are conducted under a stereo-microscope, and with a robot-controlled surgical tool.
Crossing Nets: Combining GANs and VAEs with a Shared Latent Space for Hand Pose Estimation
Regressing the hand pose can then be done by learning a discriminator to estimate the posterior of the latent pose given some depth maps.
Deep Learning on Lie Groups for Skeleton-based Action Recognition
In recent years, skeleton-based action recognition has become a popular 3D classification problem.
