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Found 30 papers, 10 papers with code
Proposal-based Video Completion
Video inpainting is an important technique for a wide variety of applications from video content editing to video restoration.
Searching for Two-Stream Models in Multivariate Space for Video Recognition
We design a multivariate search space, including 6 search variables to capture a wide variety of choices in designing two-stream models.
Voxel-wise Cross-Volume Representation Learning for 3D Neuron Reconstruction
Recently, a series of deep learning based segmentation methods have been proposed to improve the quality of raw 3D optical image stacks by removing noises and restoring neuronal structures from low-contrast background.
Towards Understanding the Effectiveness of Attention Mechanism
Instead, we verify the crucial role of feature map multiplication in attention mechanism and uncover a fundamental impact of feature map multiplication on the learned landscapes of CNNs: with the high order non-linearity brought by the feature map multiplication, it played a regularization role on CNNs, which made them learn smoother and more stable landscapes near real samples compared to vanilla CNNs.
Unidentified Video Objects: A Benchmark for Dense, Open-World Segmentation
Current state-of-the-art object detection and segmentation methods work well under the closed-world assumption.
Beyond Short Clips: End-to-End Video-Level Learning with Collaborative Memories
The standard way of training video models entails sampling at each iteration a single clip from a video and optimizing the clip prediction with respect to the video-level label.
Is Space-Time Attention All You Need for Video Understanding?
We present a convolution-free approach to video classification built exclusively on self-attention over space and time.
Ranked #2 on
Video Question Answering
on Howto100M-QA
Single Neuron Segmentation using Graph-based Global Reasoning with Auxiliary Skeleton Loss from 3D Optical Microscope Images
One of the critical steps in improving accurate single neuron reconstruction from three-dimensional (3D) optical microscope images is the neuronal structure segmentation.
From W-Net to CDGAN: Bi-temporal Change Detection via Deep Learning Techniques
Traditional change detection methods usually follow the image differencing, change feature extraction and classification framework, and their performance is limited by such simple image domain differencing and also the hand-crafted features.
CJRC: A Reliable Human-Annotated Benchmark DataSet for Chinese Judicial Reading Comprehension
We present a Chinese judicial reading comprehension (CJRC) dataset which contains approximately 10K documents and almost 50K questions with answers.
Region and Object based Panoptic Image Synthesis through Conditional GANs
Our contribution consists of the proposal of a significant task worth investigating and a naive baseline of solving it.
CAIL2019-SCM: A Dataset of Similar Case Matching in Legal Domain
In this paper, we introduce CAIL2019-SCM, Chinese AI and Law 2019 Similar Case Matching dataset.
Incorporating Graph Attention Mechanism into Knowledge Graph Reasoning Based on Deep Reinforcement Learning
Meanwhile, a novel mechanism of reinforcement learning is proposed by forcing an agent to walk forward every step to avoid the agent stalling at the same entity node constantly.
FASTER Recurrent Networks for Efficient Video Classification
FASTER aims to leverage the redundancy between neighboring clips and reduce the computational cost by learning to aggregate the predictions from models of different complexities.
Ranked #20 on
Action Recognition
on UCF101
Video Modeling with Correlation Networks
Motion is a salient cue to recognize actions in video.
Ranked #36 on
Action Classification
on Kinetics-400
Large-scale weakly-supervised pre-training for video action recognition
Second, frame-based models perform quite well on action recognition; is pre-training for good image features sufficient or is pre-training for spatio-temporal features valuable for optimal transfer learning?
Ranked #1 on
Egocentric Activity Recognition
on EPIC-KITCHENS-55
(Actions Top-1 (S2) metric)
Video Classification with Channel-Separated Convolutional Networks
It is natural to ask: 1) if group convolution can help to alleviate the high computational cost of video classification networks; 2) what factors matter the most in 3D group convolutional networks; and 3) what are good computation/accuracy trade-offs with 3D group convolutional networks.
Ranked #1 on
Action Recognition
on Sports-1M
Multi-task Learning for Chinese Word Usage Errors Detection
Chinese word usage errors often occur in non-native Chinese learners' writing.
Defeats GAN: A Simpler Model Outperforms in Knowledge Representation Learning
The goal of knowledge representation learning is to embed entities and relations into a low-dimensional, continuous vector space.
Overview of CAIL2018: Legal Judgment Prediction Competition
In this paper, we give an overview of the Legal Judgment Prediction (LJP) competition at Chinese AI and Law challenge (CAIL2018).
Scenes-Objects-Actions: A Multi-Task, Multi-Label Video Dataset
The videos retrieved by the search engines are then veried for correctness by human annotators.
CAIL2018: A Large-Scale Legal Dataset for Judgment Prediction
In this paper, we introduce the \textbf{C}hinese \textbf{AI} and \textbf{L}aw challenge dataset (CAIL2018), the first large-scale Chinese legal dataset for judgment prediction.
Devon: Deformable Volume Network for Learning Optical Flow
State-of-the-art neural network models estimate large displacement optical flow in multi-resolution and use warping to propagate the estimation between two resolutions.
Text Generation Based on Generative Adversarial Nets with Latent Variable
We propose the VGAN model where the generative model is composed of recurrent neural network and VAE.
A Closer Look at Spatiotemporal Convolutions for Action Recognition
In this paper we discuss several forms of spatiotemporal convolutions for video analysis and study their effects on action recognition.
Ranked #4 on
Action Recognition
on Sports-1M
Concept Drift Detection and Adaptation with Hierarchical Hypothesis Testing
A fundamental issue for statistical classification models in a streaming environment is that the joint distribution between predictor and response variables changes over time (a phenomenon also known as concept drifts), such that their classification performance deteriorates dramatically.
Face Aging Effect Simulation using Hidden Factor Analysis Joint Sparse Representation
Face aging simulation has received rising investigations nowadays, whereas it still remains a challenge to generate convincing and natural age-progressed face images.
A robust and efficient video representation for action recognition
We also use the homography to cancel out camera motion from the optical flow.
Concept Drift Detection for Streaming Data
Common statistical prediction models often require and assume stationarity in the data.
Active Community Detection in Massive Graphs
A canonical problem in graph mining is the detection of dense communities.
Social and Information Networks Physics and Society