Search Results for author:
Found 24 papers, 7 papers with code
FlashFace: Human Image Personalization with High-fidelity Identity Preservation
This work presents FlashFace, a practical tool with which users can easily personalize their own photos on the fly by providing one or a few reference face images and a text prompt.
Spatio-Temporal Field Neural Networks for Air Quality Inference
The air quality inference problem aims to utilize historical data from a limited number of observation sites to infer the air quality index at an unknown location.
LivePhoto: Real Image Animation with Text-guided Motion Control
In particular, considering the facts that (1) text can only describe motions roughly (e. g., regardless of the moving speed) and (2) text may include both content and motion descriptions, we introduce a motion intensity estimation module as well as a text re-weighting module to reduce the ambiguity of text-to-motion mapping.
Learning Disentangled Identifiers for Action-Customized Text-to-Image Generation
Experimental results show that existing subject-driven customization methods fail to learn the representative characteristics of actions and struggle in decoupling actions from context features, including appearance.
Check, Locate, Rectify: A Training-Free Layout Calibration System for Text-to-Image Generation
To align the generated image with layout instructions, we present a training-free layout calibration system SimM that intervenes in the generative process on the fly during inference time.
Incentive Mechanism Design for Unbiased Federated Learning with Randomized Client Participation
Incentive mechanism is crucial for federated learning (FL) when rational clients do not have the same interests in the global model as the server.
Troika: Multi-Path Cross-Modal Traction for Compositional Zero-Shot Learning
Recent compositional zero-shot learning (CZSL) methods adapt pre-trained vision-language models (VLMs) by constructing trainable prompts only for composed state-object pairs.
ViM: Vision Middleware for Unified Downstream Transferring
ViM consists of a zoo of lightweight plug-in modules, each of which is independently learned on a midstream dataset with a shared frozen backbone.
UKnow: A Unified Knowledge Protocol for Common-Sense Reasoning and Vision-Language Pre-training
This work presents a unified knowledge protocol, called UKnow, which facilitates knowledge-based studies from the perspective of data.
Grow and Merge: A Unified Framework for Continuous Categories Discovery
Although a number of studies are devoted to novel category discovery, most of them assume a static setting where both labeled and unlabeled data are given at once for finding new categories.
SsciBERT: A Pre-trained Language Model for Social Science Texts
The academic literature of social sciences records human civilization and studies human social problems.
Rethinking Supervised Pre-training for Better Downstream Transferring
Though for most cases, the pre-training stage is conducted based on supervised methods, recent works on self-supervised pre-training have shown powerful transferability and even outperform supervised pre-training on multiple downstream tasks.
Exploring Stronger Feature for Temporal Action Localization
Temporal action localization aims to localize starting and ending time with action category.
Proposal Relation Network for Temporal Action Detection
We calculate the detection results by assigning the proposals with corresponding classification results.
Ranked #2 on
Temporal Action Localization
on ActivityNet-1.3
(using extra training data)
Weakly-Supervised Temporal Action Localization Through Local-Global Background Modeling
Then our proposed Local-Global Background Modeling Network (LGBM-Net) is trained to localize instances by using only video-level labels based on Multi-Instance Learning (MIL).
Weakly-supervised Learning
Weakly-supervised Temporal Action Localization
+1
Relation Modeling in Spatio-Temporal Action Localization
This paper presents our solution to the AVA-Kinetics Crossover Challenge of ActivityNet workshop at CVPR 2021.
Ranked #4 on
Spatio-Temporal Action Localization
on AVA-Kinetics
(using extra training data)
A Stronger Baseline for Ego-Centric Action Detection
This technical report analyzes an egocentric video action detection method we used in the 2021 EPIC-KITCHENS-100 competition hosted in CVPR2021 Workshop.
Towards Training Stronger Video Vision Transformers for EPIC-KITCHENS-100 Action Recognition
In this paper, we present empirical results for training a stronger video vision transformer on the EPIC-KITCHENS-100 Action Recognition dataset.
View-Guided Point Cloud Completion
This paper presents a view-guided solution for the task of point cloud completion.
Ranked #3 on
Point Cloud Completion
on ShapeNet-ViPC
Event Stream Super-Resolution via Spatiotemporal Constraint Learning
Therefore, it is imperative to explore the algorithm of event stream super-resolution, which is a non-trivial task due to the sparsity and strong spatio-temporal correlation of the events from an event camera.
Incremental Learning on Growing Graphs
To tackle this problem, we introduce incremental graph learning (IGL), a general framework to formulate the learning on growing graphs in an incremental manner, where traditional graph learning method could be deployed as a basic model.
Design of High-Frequency Trading Algorithm Based on Machine Learning
Based on iterative optimization and activation function in deep learning, we proposed a new analytical framework of high-frequency trading information, that reduced structural loss in the assembly of Volume-synchronized probability of Informed Trading ($VPIN$), Generalized Autoregressive Conditional Heteroscedasticity (GARCH) and Support Vector Machine (SVM) to make full use of the order book information.
Trading and Market Microstructure
MeshNet: Mesh Neural Network for 3D Shape Representation
However, there is little effort on using mesh data in recent years, due to the complexity and irregularity of mesh data.
