Computer Vision – ACCV 2020

15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 – December 4, 2020, Revised Selected Papers, Part VI

AvHiroshi Ishikawa,Cheng-Lin Liu

Häftad, Engelska, 2021

Del 12627 i serien Lecture Notes in Computer Science

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Beskrivning

The six volume set of LNCS 12622-12627 constitutes the proceedings of the 15th Asian Conference on Computer Vision, ACCV 2020, held in Kyoto, Japan, in November/ December 2020.*The total of 254 contributions was carefully reviewed and selected from 768 submissions during two rounds of reviewing and improvement.

Produktinformation

Utgivningsdatum:2021-02-26
Mått:155 x 235 x 39 mm
Vikt:1 077 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:705
Förlag:Springer Nature Switzerland AG
ISBN:9783030695439

Utforska kategorier

Nätverk och kommunikation inom Data och IT
Systemvetenskap och AI inom Data och IT

Innehållsförteckning

Applications of Computer Vision, Vision for X.- Query by Strings and Return Ranking Word Regions with Only One Look.- Single-Image Camera Response Function Using Prediction Consistency and Gradual Refinement.- FootNet: An efficient convolutional network for multiview 3D foot reconstruction.- Synthetic-to-real domain adaptation for lane detection.- RAF-AU Database: In-the-Wild Facial Expressions with Subjective Emotion Judgement and Objective AU Annotations.- DoFNet: Depth of Field Difference Learning for Detecting Image Forgery.- Explaining image classifiers by removing input features using generative models.- Do We Need Sound for Sound Source Localization?.- Modular Graph Attention Network for Complex Visual Relational Reasoning.- CloTH-VTON: Clothing Three-dimensional reconstruction for Hybrid image-based Virtual Try-ON.- Multi-label X-ray Imagery Classification via Bottom-up Attention and Meta Fusion.- Learning End-to-End Action Interaction by Paired-Embedding Data Augmentation.- Sketch-to-Art: Synthesizing Stylized Art Images From Sketches.- Road Obstacle Detection Method Based on an Autoencoder with Semantic Segmentation.- SpotPatch: Parameter-Efficient Transfer Learning for Mobile Object Detection.- Trainable Structure Tensors for Autonomous Baggage Threat Detection Under Extreme Occlusion.- Audiovisual Transformer with Instance Attention for Audio-Visual Event Localization.- Watch, read and lookup: learning to spot signs from multiple supervisors.- Domain-transferred Face Augmentation Network.- Pose Correction Algorithm for Relative Frames between Keyframes in SLAM.- Dense-Scale Feature Learning in Person Re-Identification.- Class-incremental Learning with Rectified Feature-Graph Preservation.- Patch SVDD: Patch-level SVDD for Anomaly Detection and Segmentation.- Towards Robust Fine-grained Recognition by Maximal Separation of Discriminative Features.- Visually Guided Sound Source Separation using Cascaded Opponent Filter Network.- Channel Recurrent Attention Networks for Video Pedestrian Retrieval.- In Defense of LSTMs for Addressing Multiple Instance Learning Problems.- Addressing Class Imbalance in Scene Graph Parsing by Learning to Contrast and Score.- Show, Conceive and Tell: Image Captioning with Prospective Linguistic Information.- Datasets and Performance Analysis.- RGB-T Crowd Counting from Drone: A Benchmark and MMCCN Network.- Webly Supervised Semantic Embeddings for Large Scale Zero-Shot Learning.- Compensating for the Lack of Extra Training Data by Learning Extra Representation.- Class-Wise Difficulty-Balanced Loss for Solving Class-Imbalance.- OpenTraj: Assessing Prediction Complexity in Human Trajectories Datasets.- Pre-training without Natural Images.- TTPLA: An Aerial-Image Dataset for Detection and Segmentation of Transmission Towers and Power Lines.- A Day on Campus - An Anomaly Detection Dataset for Events in a Single Camera.- A Benchmark and Baseline for Language-Driven Image Editing.- Self-supervised Learning of Orc-Bert Augmentator for Recognizing Few-Shot Oracle Characters.- Understanding Motion in Sign Language: A New Structured Translation Dataset.- FreezeNet: Full Performance by Reduced Storage Costs.