Search Results for author:
Found 25 papers, 6 papers with code
Uncertainty in the financial market and application to forecastabnormal financial fluctuations
The integration and innovation of finance and technology have gradually transformed the financial system into a complex one.
Debiasing Text-to-Image Diffusion Models
Despite its simplicity, we show that IDA shows efficiency and fast convergence in resolving the social bias in TTI diffusion models.
Dataset Condensation via Generative Model
Dataset condensation aims to condense a large dataset with a lot of training samples into a small set.
DiffCloth: Diffusion Based Garment Synthesis and Manipulation via Structural Cross-modal Semantic Alignment
Cross-modal garment synthesis and manipulation will significantly benefit the way fashion designers generate garments and modify their designs via flexible linguistic interfaces. Current approaches follow the general text-to-image paradigm and mine cross-modal relations via simple cross-attention modules, neglecting the structural correspondence between visual and textual representations in the fashion design domain.
Free-ATM: Exploring Unsupervised Learning on Diffusion-Generated Images with Free Attention Masks
Despite the rapid advancement of unsupervised learning in visual representation, it requires training on large-scale datasets that demand costly data collection, and pose additional challenges due to concerns regarding data privacy.
Lowis3D: Language-Driven Open-World Instance-Level 3D Scene Understanding
To address this challenge, we propose to harness pre-trained vision-language (VL) foundation models that encode extensive knowledge from image-text pairs to generate captions for multi-view images of 3D scenes.
Ranked #3 on
3D Open-Vocabulary Instance Segmentation
on S3DIS
3D Open-Vocabulary Instance Segmentation
Instance Segmentation
+4
DragDiffusion: Harnessing Diffusion Models for Interactive Point-based Image Editing
In this work, we extend this editing framework to diffusion models and propose a novel approach DragDiffusion.
Fixed-point iterative algorithm for SVI model
In this study, we develop an efficient iterative algorithm for the SVI model based on a fixed-point and least-square optimizer.
PV3D: A 3D Generative Model for Portrait Video Generation
While some prior works have applied such image GANs to unconditional 2D portrait video generation and static 3D portrait synthesis, there are few works successfully extending GANs for generating 3D-aware portrait videos.
PLA: Language-Driven Open-Vocabulary 3D Scene Understanding
Open-vocabulary scene understanding aims to localize and recognize unseen categories beyond the annotated label space.
Ranked #2 on
3D Open-Vocabulary Instance Segmentation
on S3DIS
3D Open-Vocabulary Instance Segmentation
Contrastive Learning
+4
Data-based Polymer-Unit Fingerprint (PUFp): A Newly Accessible Expression of Polymer Organic Semiconductors for Machine Learning
By investigating the combinations of polymer units with mobility performance, a scheme for designing polymer OSC materials by combining ML approaches and PUFp information is proposed to not only passively predict OSC mobility but also actively provide structural guidance for new high-mobility OSC material design.
Is synthetic data from generative models ready for image recognition?
Recent text-to-image generation models have shown promising results in generating high-fidelity photo-realistic images.
Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning
To remedy this problem caused by the data heterogeneity, we propose {\sc FedDecorr}, a novel method that can effectively mitigate dimensional collapse in federated learning.
1st Place Solution to ECCV 2022 Challenge on Out of Vocabulary Scene Text Understanding: End-to-End Recognition of Out of Vocabulary Words
Our oCLIP-based model achieves 28. 59\% in h-mean which ranks 1st in end-to-end OOV word recognition track of OOV Challenge in ECCV2022 TiE Workshop.
Runner-Up Solution to ECCV 2022 Challenge on Out of Vocabulary Scene Text Understanding: Cropped Word Recognition
This report presents our 2nd place solution to ECCV 2022 challenge on Out-of-Vocabulary Scene Text Understanding (OOV-ST) : Cropped Word Recognition.
VMRF: View Matching Neural Radiance Fields
With the feature transport plan as the guidance, a novel pose calibration technique is designed which rectifies the initially randomized camera poses by predicting relative pose transformations between the pair of rendered and real images.
Few Could Be Better Than All: Feature Sampling and Grouping for Scene Text Detection
Different from previous approaches that learn robust deep representations of scene text in a holistic manner, our method performs scene text detection based on a few representative features, which avoids the disturbance by background and reduces the computational cost.
Ranked #21 on
Object Detection In Aerial Images
on DOTA
(using extra training data)
Language Matters: A Weakly Supervised Vision-Language Pre-training Approach for Scene Text Detection and Spotting
Our network consists of an image encoder and a character-aware text encoder that extract visual and textual features, respectively, as well as a visual-textual decoder that models the interaction among textual and visual features for learning effective scene text representations.
Optical Character Recognition
Optical Character Recognition (OCR)
+2
SeqFormer: Sequential Transformer for Video Instance Segmentation
Nevertheless, we observe that a stand-alone instance query suffices for capturing a time sequence of instances in a video, but attention mechanisms shall be done with each frame independently.
Ranked #2 on
Video Instance Segmentation
on HQ-YTVIS
Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence
Artificial intelligence (AI) provides a promising substitution for streamlining COVID-19 diagnoses.
Contextual Text Detection
This paper presents Contextual Text Detection, a new setup that detects contextual text blocks for better understanding of texts in scenes.
I2C2W: Image-to-Character-to-Word Transformers for Accurate Scene Text Recognition
The first task focuses on image-to-character (I2C) mapping which detects a set of character candidates from images based on different alignments of visual features in an non-sequential way.
Scene Text Detection with Scribble Lines
It is a general labeling method for texts with various shapes and requires low labeling costs.
FedOCR: Communication-Efficient Federated Learning for Scene Text Recognition
In this paper, we study how to make use of decentralized datasets for training a robust scene text recognizer while keeping them stay on local devices.
FIS-GAN: GAN with Flow-based Importance Sampling
Generative Adversarial Networks (GAN) training process, in most cases, apply Uniform or Gaussian sampling methods in the latent space, which probably spends most of the computation on examples that can be properly handled and easy to generate.
