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Found 20 papers, 5 papers with code
A deep neural network framework for dynamic multi-valued mapping estimation and its applications
The objective is to model the dynamic multi-valued mapping between the input and output by providing a reliable uncertainty measurement.
AdaFedFR: Federated Face Recognition with Adaptive Inter-Class Representation Learning
With the growing attention on data privacy and communication security in face recognition applications, federated learning has been introduced to learn a face recognition model with decentralized datasets in a privacy-preserving manner.
CHOSEN: Contrastive Hypothesis Selection for Multi-View Depth Refinement
We propose CHOSEN, a simple yet flexible, robust and effective multi-view depth refinement framework.
MagicMirror: Fast and High-Quality Avatar Generation with a Constrained Search Space
We introduce a novel framework for 3D human avatar generation and personalization, leveraging text prompts to enhance user engagement and customization.
SWBT: Similarity Weighted Behavior Transformer with the Imperfect Demonstration for Robotic Manipulation
Imitation learning (IL), aiming to learn optimal control policies from expert demonstrations, has been an effective method for robot manipulation tasks.
Gaussian3Diff: 3D Gaussian Diffusion for 3D Full Head Synthesis and Editing
We present a novel framework for generating photorealistic 3D human head and subsequently manipulating and reposing them with remarkable flexibility.
LatentWarp: Consistent Diffusion Latents for Zero-Shot Video-to-Video Translation
As a result, the corresponding regions across the adjacent frames can share closely-related query tokens and attention outputs, which can further improve latent-level consistency to enhance visual temporal coherence of generated videos.
Learning Personalized High Quality Volumetric Head Avatars from Monocular RGB Videos
The learnt avatar is driven by a parametric face model to achieve user-controlled facial expressions and head poses.
Learn to Cluster Faces via Pairwise Classification
However, they usually suffer from excessive memory consumption especially on large-scale graphs, and rely on empirical thresholds to determine the connectivities between samples in inference, which restricts their applications in various real-world scenes.
CelebA-Spoof Challenge 2020 on Face Anti-Spoofing: Methods and Results
It is the largest face anti-spoofing dataset in terms of the numbers of the data and the subjects.
Modal Uncertainty Estimation via Discrete Latent Representations
Many important problems in the real world don't have unique solutions.
Guided Collaborative Training for Pixel-wise Semi-Supervised Learning
Although SSL methods have achieved impressive results in image classification, the performances of applying them to pixel-wise tasks are unsatisfactory due to their need for dense outputs.
Towards Geometry Guided Neural Relighting with Flash Photography
By incorporating the depth map, our approach is able to extrapolate realistic high-frequency effects under novel lighting via geometry guided image decomposition from the flashlight image, and predict the cast shadow map from the shadow-encoding transformed depth map.
Gradient Regularized Contrastive Learning for Continual Domain Adaptation
At the core of our method, gradient regularization plays two key roles: (1) enforces the gradient of contrastive loss not to increase the supervised training loss on the source domain, which maintains the discriminative power of learned features; (2) regularizes the gradient update on the new domain not to increase the classification loss on the old target domains, which enables the model to adapt to an in-coming target domain while preserving the performance of previously observed domains.
Modal Uncertainty Estimation via Discrete Latent Representation
We motivate our use of discrete latent space through the multi-modal posterior collapse problem in current conditional generative models, then develop the theoretical background, and extensively validate our method on both synthetic and realistic tasks.
Adapting Object Detectors with Conditional Domain Normalization
Then this domain-vector is used to encode the features from another domain through a conditional normalization, resulting in different domains' features carrying the same domain attribute.
Ranked #1 on
Unsupervised Domain Adaptation
on SIM10K to BDD100K
Shape analysis via inconsistent surface registration
In this work, we develop a framework for shape analysis using inconsistent surface mapping.
Deep End-to-End Alignment and Refinement for Time-of-Flight RGB-D Module
Recently, it is increasingly popular to equip mobile RGB cameras with Time-of-Flight (ToF) sensors for active depth sensing.
Inconsistent Surface Registration via Optimization of Mapping Distortions
Mapping distortions are described by the Beltrami coefficient as well as the differential of the mapping.
Computational Geometry Graphics
Computing quasiconformal folds
We propose a novel way of computing surface folding maps via solving a linear PDE.
Computational Geometry
