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Found 18 papers, 12 papers with code
Learning Rotation for Kernel Correlation Filter
Kernel Correlation Filters have shown a very promising scheme for visual tracking in terms of speed and accuracy on several benchmarks.
SADA: Semantic Adversarial Diagnostic Attacks for Autonomous Applications
In contrast, we present a general framework for adversarial attacks on trained agents, which covers semantic perturbations to the environment of the agent performing the task as well as pixel-level attacks.
Towards Analyzing Semantic Robustness of Deep Neural Networks
Despite the impressive performance of Deep Neural Networks (DNNs) on various vision tasks, they still exhibit erroneous high sensitivity toward semantic primitives (e. g. object pose).
IAN: Combining Generative Adversarial Networks for Imaginative Face Generation
Generative Adversarial Networks (GANs) have gained momentum for their ability to model image distributions.
Expected Tight Bounds for Robust Training
In this paper, we closely examine the bounds of a block of layers composed in the form of Affine-ReLU-Affine.
Expected Tight Bounds for Robust Deep Neural Network Training
al. that bounded input intervals can be inexpensively propagated from layer to layer through deep networks.
AdvPC: Transferable Adversarial Perturbations on 3D Point Clouds
Our proposed attack increases the attack success rate by up to 40% for those transferred to unseen networks (transferability), while maintaining a high success rate on the attacked network.
MVTN: Multi-View Transformation Network for 3D Shape Recognition
MVTN exhibits clear performance gains in the tasks of 3D shape classification and 3D shape retrieval without the need for extra training supervision.
Ranked #1 on
3D Object Retrieval
on ModelNet40
Voint Cloud: Multi-View Point Cloud Representation for 3D Understanding
To this end, we introduce the concept of the multi-view point cloud (Voint cloud), representing each 3D point as a set of features extracted from several view-points.
Pix4Point: Image Pretrained Standard Transformers for 3D Point Cloud Understanding
Pretrained on a large number of widely available images, significant gains of PViT are observed in the tasks of 3D point cloud classification, part segmentation, and semantic segmentation on ScanObjectNN, ShapeNetPart, and S3DIS, respectively.
Estimating more camera poses for ego-centric videos is essential for VQ3D
Visual queries 3D localization (VQ3D) is a task in the Ego4D Episodic Memory Benchmark.
EgoLoc: Revisiting 3D Object Localization from Egocentric Videos with Visual Queries
Yet, we point out that the low number of camera poses caused by camera re-localization from previous VQ3D methods severally hinders their overall success rate.
SPARF: Large-Scale Learning of 3D Sparse Radiance Fields from Few Input Images
SuRFNet employs partial SRFs from few/one images and a specialized SRF loss to learn to generate high-quality sparse voxel radiance fields that can be rendered from novel views.
MVTN: Learning Multi-View Transformations for 3D Understanding
Multi-view projection techniques have shown themselves to be highly effective in achieving top-performing results in the recognition of 3D shapes.
VARS: Video Assistant Referee System for Automated Soccer Decision Making from Multiple Views
The Video Assistant Referee (VAR) has revolutionized association football, enabling referees to review incidents on the pitch, make informed decisions, and ensure fairness.
Mindstorms in Natural Language-Based Societies of Mind
What should be the social structure of an NLSOM?
Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors
We present Magic123, a two-stage coarse-to-fine approach for high-quality, textured 3D meshes generation from a single unposed image in the wild using both2D and 3D priors.
GES: Generalized Exponential Splatting for Efficient Radiance Field Rendering
With the aid of a frequency-modulated loss, GES achieves competitive performance in novel-view synthesis benchmarks while requiring less than half the memory storage of Gaussian Splatting and increasing the rendering speed by up to 39%.
