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05/23/2023
Control-A-Video: Controllable Text-to-Video Generation with Diffusion Models
This paper presents a controllable text-to-video (T2V) diffusion model, ...
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05/06/2023
Multi-object Video Generation from Single Frame Layouts
In this paper, we study video synthesis with emphasis on simplifying the...
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11/15/2022
Category-Adaptive Label Discovery and Noise Rejection for Multi-label Image Recognition with Partial Positive Labels
As a promising solution of reducing annotation cost, training multi-labe...
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04/08/2022
Semantic Representation and Dependency Learning for Multi-Label Image Recognition
Recently many multi-label image recognition (MLR) works have made signif...
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03/04/2022
Semantic-Aware Representation Blending for Multi-Label Image Recognition with Partial Labels
Training the multi-label image recognition models with partial labels, i...
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12/21/2021
Structured Semantic Transfer for Multi-Label Recognition with Partial Labels
Multi-label image recognition is a fundamental yet practical task becaus...
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12/29/2020
AU-Expression Knowledge Constrained Representation Learning for Facial Expression Recognition
Recognizing human emotion/expressions automatically is quite an expected...
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12/08/2020
Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd Counting
Crowd counting is a fundamental yet challenging problem, which desires r...
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09/20/2020
Knowledge-Guided Multi-Label Few-Shot Learning for General Image Recognition
Recognizing multiple labels of an image is a practical yet challenging t...
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08/03/2020
Active Object Search
In this work, we investigate an Active Object Search (AOS) task that is ...
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08/03/2020
Adversarial Graph Representation Adaptation for Cross-Domain Facial Expression Recognition
Data inconsistency and bias are inevitable among different facial expres...
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07/21/2020
Fine-Grained Image Captioning with Global-Local Discriminative Objective
Significant progress has been made in recent years in image captioning, ...
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03/23/2020
Efficient Crowd Counting via Structured Knowledge Transfer
Crowd counting is an application-oriented task and its inference efficie...
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01/14/2020
Physical-Virtual Collaboration Graph Network for Station-Level Metro Ridership Prediction
Due to the widespread applications in real-world scenarios, metro riders...
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11/21/2019
Knowledge Graph Transfer Network for Few-Shot Recognition
Few-shot learning aims to learn novel categories from very few samples g...
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08/20/2019
Learning Semantic-Specific Graph Representation for Multi-Label Image Recognition
Recognizing multiple labels of images is a practical and challenging tas...
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05/29/2019
Instance-Aware Representation Learning and Association for Online Multi-Person Tracking
Multi-Person Tracking (MPT) is often addressed within the detection-to-a...
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11/29/2018
ADCrowdNet: An Attention-injective Deformable Convolutional Network for Crowd Understanding
We propose an attention-injective deformable convolutional network calle...
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01/20/2018
Structured Inhomogeneous Density Map Learning for Crowd Counting
In this paper, we aim at tackling the problem of crowd counting in extre...
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12/29/2017
