Search Results for author:
Found 20 papers, 9 papers with code
AMERICANO: Argument Generation with Discourse-driven Decomposition and Agent Interaction
Argument generation is a challenging task in natural language processing, which requires rigorous reasoning and proper content organization.
Camouflaged Image Synthesis Is All You Need to Boost Camouflaged Detection
This approach can serve as a plug-and-play data generation and augmentation module for existing camouflaged object detection tasks and provides a novel way to introduce more diversity and distributions into current camouflage datasets.
NeRFInvertor: High Fidelity NeRF-GAN Inversion for Single-shot Real Image Animation
Furthermore, our method leverages explicit and implicit 3D regularizations using the in-domain neighborhood samples around the optimized latent code to remove geometrical and visual artifacts.
Semi-supervised Domain Adaptive Structure Learning
Semi-supervised domain adaptation (SSDA) is quite a challenging problem requiring methods to overcome both 1) overfitting towards poorly annotated data and 2) distribution shift across domains.
Context-Aware Interaction Network for Question Matching
Impressive milestones have been achieved in text matching by adopting a cross-attention mechanism to capture pertinent semantic connections between two sentence representations.
Quality meets Diversity: A Model-Agnostic Framework for Computerized Adaptive Testing
In this paper, we study a novel model-agnostic CAT problem, where we aim to propose a flexible framework that can adapt to different cognitive models.
Multimodal In-bed Pose and Shape Estimation under the Blankets
Typically, humans are covered by a blanket when resting, for which we propose a multimodal approach to uncover the subjects so their bodies at rest can be viewed without the occlusion of the blankets above.
SuperFront: From Low-resolution to High-resolution Frontal Face Synthesis
Even as impressive milestones are achieved in synthesizing faces, the importance of preserving identity is needed in practice and should not be overlooked.
Collaborative Attention Mechanism for Multi-View Action Recognition
Extensive experiments on four action datasets illustrate the proposed CAM achieves better results for each view and also boosts multi-view performance.
Families In Wild Multimedia: A Multimodal Database for Recognizing Kinship
Thus, to narrow the gap between research and reality and enhance the power of kinship recognition systems, we extend FIW with multimedia (MM) data (i. e., video, audio, and text captions).
Dual-Attention GAN for Large-Pose Face Frontalization
Face frontalization provides an effective and efficient way for face data augmentation and further improves the face recognition performance in extreme pose scenario.
Recognizing Families In the Wild: White Paper for the 4th Edition Data Challenge
Recognizing Families In the Wild (RFIW): an annual large-scale, multi-track automatic kinship recognition evaluation that supports various visual kin-based problems on scales much higher than ever before.
Contradictory Structure Learning for Semi-supervised Domain Adaptation
Current adversarial adaptation methods attempt to align the cross-domain features, whereas two challenges remain unsolved: 1) the conditional distribution mismatch and 2) the bias of the decision boundary towards the source domain.
Joint Super-Resolution and Alignment of Tiny Faces
As for SR, the proposed method recovers sharper edges and more details from LR face images than other state-of-the-art methods, which we demonstrate qualitatively and quantitatively.
Neural Cognitive Diagnosis for Intelligent Education Systems
Cognitive diagnosis is a fundamental issue in intelligent education, which aims to discover the proficiency level of students on specific knowledge concepts.
EKT: Exercise-aware Knowledge Tracing for Student Performance Prediction
In EERNN, we simply summarize each student's state into an integrated vector and trace it with a recurrent neural network, where we design a bidirectional LSTM to learn the encoding of each exercise's content.
QuesNet: A Unified Representation for Heterogeneous Test Questions
Then we propose a two-level hierarchical pre-training algorithm to learn better understanding of test questions in an unsupervised way.
Transcribing Content from Structural Images with Spotlight Mechanism
Then, we decide "what-to-write" by developing a GRU based network with the spotlight areas for transcribing the content accordingly.
Facial Expression and Peripheral Physiology Fusion to Decode Individualized Affective Experience
In this paper, we present a multimodal approach to simultaneously analyze facial movements and several peripheral physiological signals to decode individualized affective experiences under positive and negative emotional contexts, while considering their personalized resting dynamics.
In-Bed Pose Estimation: Deep Learning with Shallow Dataset
Using the HOG rectification method, the pose estimation performance of CPM significantly improved by 26. 4% in PCK0. 1 criteria compared to the model without such rectification.
