Search Results for author:
Found 30 papers, 14 papers with code
Ensemble Quadratic Assignment Network for Graph Matching
In this paper, we propose a graph neural network (GNN) based approach to combine the advantages of data-driven and traditional methods.
GeoEval: Benchmark for Evaluating LLMs and Multi-Modal Models on Geometry Problem-Solving
Yet, their proficiency in tackling geometry math problems, which necessitates an integrated understanding of both textual and visual information, has not been thoroughly evaluated.
LANS: A Layout-Aware Neural Solver for Plane Geometry Problem
Existing neural solvers take GPS as a vision-language task but are short in the representation of geometry diagrams that carry rich and complex layout information.
ToonTalker: Cross-Domain Face Reenactment
Moreover, since no paired data is provided, we propose a novel cross-domain training scheme using data from two domains with the designed analogy constraint.
NOFA: NeRF-based One-shot Facial Avatar Reconstruction
In this work, we propose a one-shot 3D facial avatar reconstruction framework that only requires a single source image to reconstruct a high-fidelity 3D facial avatar.
Efficient Text-Guided 3D-Aware Portrait Generation with Score Distillation Sampling on Distribution
These elaborated designs enable our model to generate portraits with robust multi-view semantic consistency, eliminating the need for optimization-based methods.
Accelerating Diffusion Models for Inverse Problems through Shortcut Sampling
Recently, diffusion models have demonstrated a remarkable ability to solve inverse problems in an unsupervised manner.
A Multi-Modal Neural Geometric Solver with Textual Clauses Parsed from Diagram
Geometry problem solving (GPS) is a high-level mathematical reasoning requiring the capacities of multi-modal fusion and geometric knowledge application.
Ranked #1 on
Mathematical Reasoning
on PGPS9K
Visual Traffic Knowledge Graph Generation from Scene Images
Although previous works on traffic scene understanding have achieved great success, most of them stop at a lowlevel perception stage, such as road segmentation and lane detection, and few concern high-level understanding.
Generalizable Black-Box Adversarial Attack with Meta Learning
In the scenario of black-box adversarial attack, the target model's parameters are unknown, and the attacker aims to find a successful adversarial perturbation based on query feedback under a query budget.
3D GAN Inversion with Facial Symmetry Prior
It is natural to associate 3D GANs with GAN inversion methods to project a real image into the generator's latent space, allowing free-view consistent synthesis and editing, referred as 3D GAN inversion.
VideoReTalking: Audio-based Lip Synchronization for Talking Head Video Editing In the Wild
Our system disentangles this objective into three sequential tasks: (1) face video generation with a canonical expression; (2) audio-driven lip-sync; and (3) face enhancement for improving photo-realism.
MobileCodec: Neural Inter-frame Video Compression on Mobile Devices
Realizing the potential of neural video codecs on mobile devices is a big technological challenge due to the computational complexity of deep networks and the power-constrained mobile hardware.
Learning Quality-aware Dynamic Memory for Video Object Segmentation
However, they mainly focus on better matching between the current frame and the memory frames without explicitly paying attention to the quality of the memory.
Ranked #11 on
Semi-Supervised Video Object Segmentation
on DAVIS 2016
(using extra training data)
PGDP5K: A Diagram Parsing Dataset for Plane Geometry Problems
An appropriate dataset is critical for the research of PGDP.
Plane Geometry Diagram Parsing
Geometry diagram parsing plays a key role in geometry problem solving, wherein the primitive extraction and relation parsing remain challenging due to the complex layout and between-primitive relationship.
Ranked #1 on
Scene Parsing
on PGDP5K
Document Dewarping with Control Points
In this paper, we propose a simple yet effective approach to rectify distorted document image by estimating control points and reference points.
StyleHEAT: One-Shot High-Resolution Editable Talking Face Generation via Pre-trained StyleGAN
Our framework elevates the resolution of the synthesized talking face to 1024*1024 for the first time, even though the training dataset has a lower resolution.
Real-Time, Accurate, and Consistent Video Semantic Segmentation via Unsupervised Adaptation and Cross-Unit Deployment on Mobile Device
Such a deployment scheme best utilizes the available processing power on the smartphone and enables real-time operation of our adaptive video segmentation algorithm.
Identity-guided Face Generation with Multi-modal Contour Conditions
Concretely, we propose a novel dual-encoder architecture, in which an identity encoder extracts the identity-related feature, accompanied by a main encoder to obtain the rough contour information and further fuse all the information together.
Prototype Augmentation and Self-Supervision for Incremental Learning
Despite the impressive performance in many individual tasks, deep neural networks suffer from catastrophic forgetting when learning new tasks incrementally.
Semantic-Aware Video Text Detection
To overcome the lack of character-level annotations, we propose a novel weakly-supervised character center detection module, which only uses word-level annotated real images to generate character-level labels.
Dewarping Document Image By Displacement Flow Estimation with Fully Convolutional Network
As camera-based documents are increasingly used, the rectification of distorted document images becomes a need to improve the recognition performance.
Weakly-Supervised Arbitrary-Shaped Text Detection with Expectation-Maximization Algorithm
We propose an Expectation-Maximization (EM) based weakly-supervised learning framework to train an accurate arbitrary-shaped text detector using only a small amount of polygon-level annotated data combined with a large amount of weakly annotated data.
Multi-task Layout Analysis for Historical Handwritten Documents Using Fully Convolutional Networks
Layout analysis is a fundamental process in document image analysis and understanding.
SCAN: Sliding Convolutional Attention Network for Scene Text Recognition
Scene text recognition has drawn great attentions in the community of computer vision and artificial intelligence due to its challenges and wide applications.
Robust Classification with Convolutional Prototype Learning
To improve the robustness, we propose a novel learning framework called convolutional prototype learning (CPL).
Scene Text Recognition with Sliding Convolutional Character Models
In this paper, we investigate the intrinsic characteristics of text recognition, and inspired by human cognition mechanisms in reading texts, we propose a scene text recognition method with character models on convolutional feature map.
Deep Direct Regression for Multi-Oriented Scene Text Detection
To verify this point of view, we propose a deep direct regression based method for multi-oriented scene text detection.
Drawing and Recognizing Chinese Characters with Recurrent Neural Network
In this paper, we propose a framework by using the recurrent neural network (RNN) as both a discriminative model for recognizing Chinese characters and a generative model for drawing (generating) Chinese characters.
