Search Results for author:
Found 23 papers, 10 papers with code
TelTrans: Applying Multi-Type Telecom Data to Transportation Evaluation and Prediction via Multifaceted Graph Modeling
To address the limitations of traffic prediction from location-bound detectors, we present Geographical Cellular Traffic (GCT) flow, a novel data source that leverages the extensive coverage of cellular traffic to capture mobility patterns.
Unsupervised Adversarial Detection without Extra Model: Training Loss Should Change
Adversarial robustness poses a critical challenge in the deployment of deep learning models for real-world applications.
Language Models are Causal Knowledge Extractors for Zero-shot Video Question Answering
Causal Video Question Answering (CVidQA) queries not only association or temporal relations but also causal relations in a video.
Learning Fine-Grained Visual Understanding for Video Question Answering via Decoupling Spatial-Temporal Modeling
While recent large-scale video-language pre-training made great progress in video question answering, the design of spatial modeling of video-language models is less fine-grained than that of image-language models; existing practices of temporal modeling also suffer from weak and noisy alignment between modalities.
Fair Robust Active Learning by Joint Inconsistency
Fairness and robustness play vital roles in trustworthy machine learning.
MonoDTR: Monocular 3D Object Detection with Depth-Aware Transformer
Moreover, different from conventional pixel-wise positional encodings, we introduce a novel depth positional encoding (DPE) to inject depth positional hints into transformers.
Stage Conscious Attention Network (SCAN) : A Demonstration-Conditioned Policy for Few-Shot Imitation
(3) Learning from a different expert.
Anomaly-Aware Semantic Segmentation by Leveraging Synthetic-Unknown Data
We design a new Masked Gradient Update (MGU) module to generate auxiliary data along the boundary of in-distribution data points.
Multivariate and Propagation Graph Attention Network for Spatial-Temporal Prediction with Outdoor Cellular Traffic
Furthermore, we propose a new model for multivariate spatial-temporal prediction, mainly consisting of two extending graph attention networks (GAT).
TrUMAn: Trope Understanding in Movies and Animations
By coping with the trope understanding task and enabling the deep cognition skills of machines, data mining applications and algorithms could be taken to the next level.
ReDAL: Region-based and Diversity-aware Active Learning for Point Cloud Semantic Segmentation
Despite the success of deep learning on supervised point cloud semantic segmentation, obtaining large-scale point-by-point manual annotations is still a significant challenge.
S3: Learnable Sparse Signal Superdensity for Guided Depth Estimation
Dense depth estimation plays a key role in multiple applications such as robotics, 3D reconstruction, and augmented reality.
Class-agnostic-Few-shot-Object-Counting
Instead of counting a pre-defined class, our model is able to count instances based on input reference images and reduces the huge cost of data collection, training and parameter tuning for each new object class.
Learning from 2D: Contrastive Pixel-to-Point Knowledge Transfer for 3D Pretraining
Most 3D neural networks are trained from scratch owing to the lack of large-scale labeled 3D datasets.
OCID-Ref: A 3D Robotic Dataset with Embodied Language for Clutter Scene Grounding
To effectively apply robots in working environments and assist humans, it is essential to develop and evaluate how visual grounding (VG) can affect machine performance on occluded objects.
$S^3$: Learnable Sparse Signal Superdensity for Guided Depth Estimation
Dense depth estimation plays a key role in multiple applications such as robotics, 3D reconstruction, and augmented reality.
Dual-Awareness Attention for Few-Shot Object Detection
While recent progress has significantly boosted few-shot classification (FSC) performance, few-shot object detection (FSOD) remains challenging for modern learning systems.
Ranked #9 on
Few-Shot Object Detection
on MS-COCO (10-shot)
Situation and Behavior Understanding by Trope Detection on Films
Experimental result demonstrates that modern models including BERT contextual embedding, movie tag prediction systems, and relational networks, perform at most 37% of human performance (23. 97/64. 87) in terms of F1 score.
End-to-End Video Question-Answer Generation with Generator-Pretester Network
Furthermore, using our generated QA pairs only on the Video QA task, we can surpass some supervised baselines.
GDN: A Coarse-To-Fine (C2F) Representation for End-To-End 6-DoF Grasp Detection
We proposed an end-to-end grasp detection network, Grasp Detection Network (GDN), cooperated with a novel coarse-to-fine (C2F) grasp representation design to detect diverse and accurate 6-DoF grasps based on point clouds.
Expanding Sparse Guidance for Stereo Matching
The performance of image based stereo estimation suffers from lighting variations, repetitive patterns and homogeneous appearance.
Video Question Generation via Cross-Modal Self-Attention Networks Learning
We introduce a novel task, Video Question Generation (Video QG).
