Search Results for author: Jie Song

Found 93 papers, 51 papers with code

GraspXL: Generating Grasping Motions for Diverse Objects at Scale

no code implementations28 Mar 2024 HUI ZHANG, Sammy Christen, Zicong Fan, Otmar Hilliges, Jie Song

Moreover, we show that our framework can be deployed to different dexterous hands and work with reconstructed or generated objects.

Object

On the Concept Trustworthiness in Concept Bottleneck Models

1 code implementation21 Mar 2024 Qihan Huang, Jie Song, Jingwen Hu, Haofei Zhang, Yong Wang, Mingli Song

Concept Bottleneck Models (CBMs), which break down the reasoning process into the input-to-concept mapping and the concept-to-label prediction, have garnered significant attention due to their remarkable interpretability achieved by the interpretable concept bottleneck.

Pre-Trained Model Recommendation for Downstream Fine-tuning

no code implementations11 Mar 2024 Jiameng Bai, Sai Wu, Jie Song, Junbo Zhao, Gang Chen

As a fundamental problem in transfer learning, model selection aims to rank off-the-shelf pre-trained models and select the most suitable one for the new target task.

Inductive Bias Model Selection +1

Training-Free Pretrained Model Merging

1 code implementation4 Mar 2024 Zhengqi Xu, Ke Yuan, Huiqiong Wang, Yong Wang, Mingli Song, Jie Song

Furthermore, the visualization of the merged model within the multi-task loss landscape reveals that MuDSC enables the merged model to reside in the overlapping segment, featuring a unified lower loss for each task.

Powerformer: A Section-adaptive Transformer for Power Flow Adjustment

no code implementations5 Jan 2024 KaiXuan Chen, Wei Luo, Shunyu Liu, Yaoquan Wei, Yihe Zhou, Yunpeng Qing, Quan Zhang, Jie Song, Mingli Song

In this paper, we present a novel transformer architecture tailored for learning robust power system state representations, which strives to optimize power dispatch for the power flow adjustment across different transmission sections.

Agent-Aware Training for Agent-Agnostic Action Advising in Deep Reinforcement Learning

no code implementations28 Nov 2023 Yaoquan Wei, Shunyu Liu, Jie Song, Tongya Zheng, KaiXuan Chen, Yong Wang, Mingli Song

Instead, we employ a proxy model to extract state features that are both discriminative (adaptive to the agent) and generally applicable (robust to agent noise).

Atari Games

SiTH: Single-view Textured Human Reconstruction with Image-Conditioned Diffusion

no code implementations27 Nov 2023 Hsuan-I Ho, Jie Song, Otmar Hilliges

For the former, we employ a powerful generative diffusion model to hallucinate unseen back-view appearance based on the input images.

3D Human Reconstruction 3D Reconstruction +1

Load Data Valuation in Multi-Energy Systems: An End-to-End Approach

no code implementations16 Nov 2023 Yangze Zhou, Qingsong Wen, Jie Song, Xueyuan Cui, Yi Wang

Accurate load forecasting serves as the foundation for the flexible operation of multi-energy systems (MES).

Data Valuation Load Forecasting

SynH2R: Synthesizing Hand-Object Motions for Learning Human-to-Robot Handovers

no code implementations9 Nov 2023 Sammy Christen, Lan Feng, Wei Yang, Yu-Wei Chao, Otmar Hilliges, Jie Song

In this paper, we introduce a framework that can generate plausible human grasping motions suitable for training the robot.

Zeroth-Order Feedback-Based Optimization for Distributed Demand Response

no code implementations1 Nov 2023 Ruiyang Jin, Yujie Tang, Jie Song

Distributed demand response is a typical distributed optimization problem that requires coordination among multiple agents to satisfy demand response requirements.

Distributed Optimization

SpikePoint: An Efficient Point-based Spiking Neural Network for Event Cameras Action Recognition

no code implementations11 Oct 2023 Hongwei Ren, Yue Zhou, Yulong Huang, Haotian Fu, Xiaopeng Lin, Jie Song, Bojun Cheng

Moreover, it also achieves SOTA performance across all methods on three datasets, utilizing approximately 0. 3\% of the parameters and 0. 5\% of power consumption employed by artificial neural networks (ANNs).

Action Recognition

ModelGiF: Gradient Fields for Model Functional Distance

1 code implementation ICCV 2023 Jie Song, Zhengqi Xu, Sai Wu, Gang Chen, Mingli Song

The last decade has witnessed the success of deep learning and the surge of publicly released trained models, which necessitates the quantification of the model functional distance for various purposes.

ArtiGrasp: Physically Plausible Synthesis of Bi-Manual Dexterous Grasping and Articulation

no code implementations7 Sep 2023 HUI ZHANG, Sammy Christen, Zicong Fan, Luocheng Zheng, Jemin Hwangbo, Jie Song, Otmar Hilliges

ArtiGrasp leverages reinforcement learning and physics simulations to train a policy that controls the global and local hand pose.

hand-object pose Object

EMDB: The Electromagnetic Database of Global 3D Human Pose and Shape in the Wild

1 code implementation ICCV 2023 Manuel Kaufmann, Jie Song, Chen Guo, Kaiyue Shen, Tianjian Jiang, Chengcheng Tang, Juan Zarate, Otmar Hilliges

EMDB is a novel dataset that contains high-quality 3D SMPL pose and shape parameters with global body and camera trajectories for in-the-wild videos.

Pose Estimation

Is Centralized Training with Decentralized Execution Framework Centralized Enough for MARL?

1 code implementation27 May 2023 Yihe Zhou, Shunyu Liu, Yunpeng Qing, KaiXuan Chen, Tongya Zheng, Yanhao Huang, Jie Song, Mingli Song

Despite the encouraging results achieved, CTDE makes an independence assumption on agent policies, which limits agents to adopt global cooperative information from each other during centralized training.

Multi-agent Reinforcement Learning reinforcement-learning +2

Learning Locally Editable Virtual Humans

no code implementations CVPR 2023 Hsuan-I Ho, Lixin Xue, Jie Song, Otmar Hilliges

To this end, we construct a trainable feature codebook to store local geometry and texture features on the vertices of a deformable body model, thus exploiting its consistent topology under articulation.

Human from Blur: Human Pose Tracking from Blurry Images

no code implementations ICCV 2023 Yiming Zhao, Denys Rozumnyi, Jie Song, Otmar Hilliges, Marc Pollefeys, Martin R. Oswald

The key idea is to tackle the inverse problem of image deblurring by modeling the forward problem with a 3D human model, a texture map, and a sequence of poses to describe human motion.

Deblurring Image Deblurring +2

Hi4D: 4D Instance Segmentation of Close Human Interaction

no code implementations CVPR 2023 Yifei Yin, Chen Guo, Manuel Kaufmann, Juan Jose Zarate, Jie Song, Otmar Hilliges

We propose Hi4D, a method and dataset for the automatic analysis of physically close human-human interaction under prolonged contact.

Instance Segmentation Semantic Segmentation

Generalization Matters: Loss Minima Flattening via Parameter Hybridization for Efficient Online Knowledge Distillation

1 code implementation CVPR 2023 Tianli Zhang, Mengqi Xue, Jiangtao Zhang, Haofei Zhang, Yu Wang, Lechao Cheng, Jie Song, Mingli Song

Most existing online knowledge distillation(OKD) techniques typically require sophisticated modules to produce diverse knowledge for improving students' generalization ability.

Knowledge Distillation

Schema Inference for Interpretable Image Classification

1 code implementation12 Mar 2023 Haofei Zhang, Mengqi Xue, Xiaokang Liu, KaiXuan Chen, Jie Song, Mingli Song

In this paper, we study a novel inference paradigm, termed as schema inference, that learns to deductively infer the explainable predictions by rebuilding the prior deep neural network (DNN) forwarding scheme, guided by the prevalent philosophical cognitive concept of schema.

Classification Graph Matching +1

X-Avatar: Expressive Human Avatars

1 code implementation CVPR 2023 Kaiyue Shen, Chen Guo, Manuel Kaufmann, Juan Jose Zarate, Julien Valentin, Jie Song, Otmar Hilliges

Our method models bodies, hands, facial expressions and appearance in a holistic fashion and can be learned from either full 3D scans or RGB-D data.

3D Human Reconstruction

Battery Valuation and Management for Battery Swapping Station with an Intertemporal Framework

no code implementations28 Feb 2023 Xinjiang Chen, Yu Yang, Jianxiao Wang, Jie Song, Guannan He

Battery swapping as a business model for battery energy storage (BES) has great potential in future integrated low-carbon energy and transportation systems.

Management

Vid2Avatar: 3D Avatar Reconstruction from Videos in the Wild via Self-supervised Scene Decomposition

1 code implementation CVPR 2023 Chen Guo, Tianjian Jiang, Xu Chen, Jie Song, Otmar Hilliges

Specifically, we define a temporally consistent human representation in canonical space and formulate a global optimization over the background model, the canonical human shape and texture, and per-frame human pose parameters.

3D Human Reconstruction Surface Reconstruction

Recent advances in artificial intelligence for retrosynthesis

no code implementations14 Jan 2023 Zipeng Zhong, Jie Song, Zunlei Feng, Tiantao Liu, Lingxiang Jia, Shaolun Yao, Tingjun Hou, Mingli Song

Afterwards, we analyze these methods in terms of their mechanism and performance, and introduce popular evaluation metrics for them, in which we also provide a detailed comparison among representative methods on several public datasets.

Multi-step retrosynthesis Retrosynthesis

InstantAvatar: Learning Avatars from Monocular Video in 60 Seconds

no code implementations CVPR 2023 Tianjian Jiang, Xu Chen, Jie Song, Otmar Hilliges

To achieve this efficiency we propose a carefully designed and engineered system, that leverages emerging acceleration structures for neural fields, in combination with an efficient empty space-skipping strategy for dynamic scenes.

An Effective Methodology for Short-Circuit Calculation of Power Systems Dominated by Power Electronics Converters Considering Unbalanced Voltage Conditions and Converter Limits

no code implementations15 Dec 2022 Jie Song, Marc Cheah-Mane, Eduardo Prieto-Araujo, Oriol Gomis-Bellmunt

A novel methodology has been presented to identify short-circuit equilibrium point of the studied system considering the operation and limitations of power converters.

Evaluation and Improvement of Interpretability for Self-Explainable Part-Prototype Networks

1 code implementation ICCV 2023 Qihan Huang, Mengqi Xue, Wenqi Huang, Haofei Zhang, Jie Song, Yongcheng Jing, Mingli Song

Part-prototype networks (e. g., ProtoPNet, ProtoTree, and ProtoPool) have attracted broad research interest for their intrinsic interpretability and comparable accuracy to non-interpretable counterparts.

Fast-SNARF: A Fast Deformer for Articulated Neural Fields

1 code implementation28 Nov 2022 Xu Chen, Tianjian Jiang, Jie Song, Max Rietmann, Andreas Geiger, Michael J. Black, Otmar Hilliges

A key challenge in making such methods applicable to articulated objects, such as the human body, is to model the deformation of 3D locations between the rest pose (a canonical space) and the deformed space.

3D Reconstruction Computational Efficiency +1

Contrastive Identity-Aware Learning for Multi-Agent Value Decomposition

1 code implementation23 Nov 2022 Shunyu Liu, Yihe Zhou, Jie Song, Tongya Zheng, KaiXuan Chen, Tongtian Zhu, Zunlei Feng, Mingli Song

Value Decomposition (VD) aims to deduce the contributions of agents for decentralized policies in the presence of only global rewards, and has recently emerged as a powerful credit assignment paradigm for tackling cooperative Multi-Agent Reinforcement Learning (MARL) problems.

Contrastive Learning SMAC+

A Survey on Explainable Reinforcement Learning: Concepts, Algorithms, Challenges

1 code implementation12 Nov 2022 Yunpeng Qing, Shunyu Liu, Jie Song, Huiqiong Wang, Mingli Song

In this survey, we provide a comprehensive review of existing works on eXplainable RL (XRL) and introduce a new taxonomy where prior works are clearly categorized into model-explaining, reward-explaining, state-explaining, and task-explaining methods.

reinforcement-learning Reinforcement Learning (RL)

Attention Diversification for Domain Generalization

1 code implementation9 Oct 2022 Rang Meng, Xianfeng Li, WeiJie Chen, Shicai Yang, Jie Song, Xinchao Wang, Lei Zhang, Mingli Song, Di Xie, ShiLiang Pu

Under this guidance, a novel Attention Diversification framework is proposed, in which Intra-Model and Inter-Model Attention Diversification Regularization are collaborated to reassign appropriate attention to diverse task-related features.

Domain Generalization

A Survey of Neural Trees

1 code implementation7 Sep 2022 Haoling Li, Jie Song, Mengqi Xue, Haofei Zhang, Jingwen Ye, Lechao Cheng, Mingli Song

This survey aims to present a comprehensive review of NTs and attempts to identify how they enhance the model interpretability.

ProtoPFormer: Concentrating on Prototypical Parts in Vision Transformers for Interpretable Image Recognition

1 code implementation22 Aug 2022 Mengqi Xue, Qihan Huang, Haofei Zhang, Lechao Cheng, Jie Song, Minghui Wu, Mingli Song

The global prototypes are adopted to provide the global view of objects to guide local prototypes to concentrate on the foreground while eliminating the influence of the background.

Decision Making Explainable artificial intelligence +1

Federated Selective Aggregation for Knowledge Amalgamation

1 code implementation27 Jul 2022 Donglin Xie, Ruonan Yu, Gongfan Fang, Jie Song, Zunlei Feng, Xinchao Wang, Li Sun, Mingli Song

The goal of FedSA is to train a student model for a new task with the help of several decentralized teachers, whose pre-training tasks and data are different and agnostic.

Learning with Recoverable Forgetting

1 code implementation17 Jul 2022 Jingwen Ye, Yifang Fu, Jie Song, Xingyi Yang, Songhua Liu, Xin Jin, Mingli Song, Xinchao Wang

Life-long learning aims at learning a sequence of tasks without forgetting the previously acquired knowledge.

General Knowledge Transfer Learning

Interaction Pattern Disentangling for Multi-Agent Reinforcement Learning

1 code implementation8 Jul 2022 Shunyu Liu, Jie Song, Yihe Zhou, Na Yu, KaiXuan Chen, Zunlei Feng, Mingli Song

In this work, we introduce a novel interactiOn Pattern disenTangling (OPT) method, to disentangle not only the joint value function into agent-wise value functions for decentralized execution, but also the entity interactions into interaction prototypes, each of which represents an underlying interaction pattern within a subgroup of the entities.

Multi-agent Reinforcement Learning reinforcement-learning +1

Ask-AC: An Initiative Advisor-in-the-Loop Actor-Critic Framework

1 code implementation5 Jul 2022 Shunyu Liu, KaiXuan Chen, Na Yu, Jie Song, Zunlei Feng, Mingli Song

Despite the promising results achieved, state-of-the-art interactive reinforcement learning schemes rely on passively receiving supervision signals from advisor experts, in the form of either continuous monitoring or pre-defined rules, which inevitably result in a cumbersome and expensive learning process.

Label Matching Semi-Supervised Object Detection

3 code implementations CVPR 2022 Binbin Chen, WeiJie Chen, Shicai Yang, Yunyi Xuan, Jie Song, Di Xie, ShiLiang Pu, Mingli Song, Yueting Zhuang

To remedy this issue, we present a novel label assignment mechanism for self-training framework, namely proposal self-assignment, which injects the proposals from student into teacher and generates accurate pseudo labels to match each proposal in the student model accordingly.

Object object-detection +2

Slimmable Domain Adaptation

1 code implementation CVPR 2022 Rang Meng, WeiJie Chen, Shicai Yang, Jie Song, Luojun Lin, Di Xie, ShiLiang Pu, Xinchao Wang, Mingli Song, Yueting Zhuang

In this paper, we introduce a simple framework, Slimmable Domain Adaptation, to improve cross-domain generalization with a weight-sharing model bank, from which models of different capacities can be sampled to accommodate different accuracy-efficiency trade-offs.

Domain Generalization Unsupervised Domain Adaptation

Learning Domain Adaptive Object Detection with Probabilistic Teacher

2 code implementations13 Jun 2022 Meilin Chen, WeiJie Chen, Shicai Yang, Jie Song, Xinchao Wang, Lei Zhang, Yunfeng Yan, Donglian Qi, Yueting Zhuang, Di Xie, ShiLiang Pu

In addition, we conduct anchor adaptation in parallel with localization adaptation, since anchor can be regarded as a learnable parameter.

Object object-detection +1

Distribution-Aware Graph Representation Learning for Transient Stability Assessment of Power System

1 code implementation12 May 2022 KaiXuan Chen, Shunyu Liu, Na Yu, Rong Yan, Quan Zhang, Jie Song, Zunlei Feng, Mingli Song

As the topology of the power system is in the form of graph structure, graph neural network based representation learning is naturally suitable for learning the status of the power system.

Binary Classification Graph Representation Learning +1

Spot-adaptive Knowledge Distillation

2 code implementations5 May 2022 Jie Song, Ying Chen, Jingwen Ye, Mingli Song

Knowledge distillation (KD) has become a well established paradigm for compressing deep neural networks.

Knowledge Distillation

Meta-attention for ViT-backed Continual Learning

1 code implementation CVPR 2022 Mengqi Xue, Haofei Zhang, Jie Song, Mingli Song

Continual learning is a longstanding research topic due to its crucial role in tackling continually arriving tasks.

Continual Learning

Root-aligned SMILES: A Tight Representation for Chemical Reaction Prediction

1 code implementation22 Mar 2022 Zipeng Zhong, Jie Song, Zunlei Feng, Tiantao Liu, Lingxiang Jia, Shaolun Yao, Min Wu, Tingjun Hou, Mingli Song

Chemical reaction prediction, involving forward synthesis and retrosynthesis prediction, is a fundamental problem in organic synthesis.

Chemical Reaction Prediction Retrosynthesis +1

Knowledge Amalgamation for Object Detection with Transformers

1 code implementation7 Mar 2022 Haofei Zhang, Feng Mao, Mengqi Xue, Gongfan Fang, Zunlei Feng, Jie Song, Mingli Song

Moreover, the transformer-based students excel in learning amalgamated knowledge, as they have mastered heterogeneous detection tasks rapidly and achieved superior or at least comparable performance to those of the teachers in their specializations.

Object object-detection +1

Dual Perceptual Loss for Single Image Super-Resolution Using ESRGAN

no code implementations17 Jan 2022 Jie Song, Huawei Yi, Wenqian Xu, Xiaohui Li, Bo Li, Yuanyuan Liu

The proposal of perceptual loss solves the problem that per-pixel difference loss function causes the reconstructed image to be overly-smooth, which acquires a significant progress in the field of single image super-resolution reconstruction.

Image Super-Resolution

gDNA: Towards Generative Detailed Neural Avatars

no code implementations CVPR 2022 Xu Chen, Tianjian Jiang, Jie Song, Jinlong Yang, Michael J. Black, Andreas Geiger, Otmar Hilliges

Furthermore, we show that our method can be used on the task of fitting human models to raw scans, outperforming the previous state-of-the-art.

Up to 100$\times$ Faster Data-free Knowledge Distillation

2 code implementations12 Dec 2021 Gongfan Fang, Kanya Mo, Xinchao Wang, Jie Song, Shitao Bei, Haofei Zhang, Mingli Song

At the heart of our approach is a novel strategy to reuse the shared common features in training data so as to synthesize different data instances.

Data-free Knowledge Distillation

Auto-Tag: Tagging-Data-By-Example in Data Lakes

no code implementations11 Dec 2021 Yeye He, Jie Song, Yue Wang, Surajit Chaudhuri, Vishal Anil, Blake Lassiter, Yaron Goland, Gaurav Malhotra

As data lakes become increasingly popular in large enterprises today, there is a growing need to tag or classify data assets (e. g., files and databases) in data lakes with additional metadata (e. g., semantic column-types), as the inferred metadata can enable a range of downstream applications like data governance (e. g., GDPR compliance), and dataset search.

TAG

Bootstrapping ViTs: Towards Liberating Vision Transformers from Pre-training

1 code implementation CVPR 2022 Haofei Zhang, Jiarui Duan, Mengqi Xue, Jie Song, Li Sun, Mingli Song

Recently, vision Transformers (ViTs) are developing rapidly and starting to challenge the domination of convolutional neural networks (CNNs) in the realm of computer vision (CV).

A Survey of Deep Learning for Low-Shot Object Detection

no code implementations6 Dec 2021 Qihan Huang, Haofei Zhang, Mengqi Xue, Jie Song, Mingli Song

Although few-shot learning and zero-shot learning have been extensively explored in the field of image classification, it is indispensable to design new methods for object detection in the data-scarce scenario since object detection has an additional challenging localization task.

Few-Shot Learning Few-Shot Object Detection +6

Safe Distillation Box

1 code implementation5 Dec 2021 Jingwen Ye, Yining Mao, Jie Song, Xinchao Wang, Cheng Jin, Mingli Song

In other words, all users may employ a model in SDB for inference, but only authorized users get access to KD from the model.

Knowledge Distillation

D-Grasp: Physically Plausible Dynamic Grasp Synthesis for Hand-Object Interactions

1 code implementation CVPR 2022 Sammy Christen, Muhammed Kocabas, Emre Aksan, Jemin Hwangbo, Jie Song, Otmar Hilliges

We introduce the dynamic grasp synthesis task: given an object with a known 6D pose and a grasp reference, our goal is to generate motions that move the object to a target 6D pose.

Motion Synthesis Object

Human Performance Capture from Monocular Video in the Wild

1 code implementation29 Nov 2021 Chen Guo, Xu Chen, Jie Song, Otmar Hilliges

In this work, we propose a method capable of capturing the dynamic 3D human shape from a monocular video featuring challenging body poses, without any additional input.

3D Human Shape Estimation Autonomous Driving

Render In-between: Motion Guided Video Synthesis for Action Interpolation

no code implementations1 Nov 2021 Hsuan-I Ho, Xu Chen, Jie Song, Otmar Hilliges

We propose to address these issues in a motion-guided frame-upsampling framework that is capable of producing realistic human motion and appearance.

Neural Rendering

Distribution Knowledge Embedding for Graph Pooling

1 code implementation29 Sep 2021 KaiXuan Chen, Jie Song, Shunyu Liu, Na Yu, Zunlei Feng, Gengshi Han, Mingli Song

A DKEPool network de facto disassembles representation learning into two stages, structure learning and distribution learning.

Representation Learning

Tree-Like Decision Distillation

no code implementations CVPR 2021 Jie Song, Haofei Zhang, Xinchao Wang, Mengqi Xue, Ying Chen, Li Sun, DaCheng Tao, Mingli Song

Knowledge distillation pursues a diminutive yet well-behaved student network by harnessing the knowledge learned by a cumbersome teacher model.

Decision Making Knowledge Distillation

Contrastive Model Inversion for Data-Free Knowledge Distillation

3 code implementations18 May 2021 Gongfan Fang, Jie Song, Xinchao Wang, Chengchao Shen, Xingen Wang, Mingli Song

In this paper, we propose Contrastive Model Inversion~(CMI), where the data diversity is explicitly modeled as an optimizable objective, to alleviate the mode collapse issue.

Contrastive Learning Data-free Knowledge Distillation

KDExplainer: A Task-oriented Attention Model for Explaining Knowledge Distillation

1 code implementation10 May 2021 Mengqi Xue, Jie Song, Xinchao Wang, Ying Chen, Xingen Wang, Mingli Song

Knowledge distillation (KD) has recently emerged as an efficacious scheme for learning compact deep neural networks (DNNs).

Knowledge Distillation Multi-class Classification

Auto-Validate: Unsupervised Data Validation Using Data-Domain Patterns Inferred from Data Lakes

no code implementations10 Apr 2021 Jie Song, Yeye He

Complex data pipelines are increasingly common in diverse applications such as BI reporting and ML modeling.

TAG

DMN4: Few-shot Learning via Discriminative Mutual Nearest Neighbor Neural Network

no code implementations15 Mar 2021 Yang Liu, Tu Zheng, Jie Song, Deng Cai, Xiaofei He

In this paper, we argue that a Mutual Nearest Neighbor (MNN) relation should be established to explicitly select the query descriptors that are most relevant to each task and discard less relevant ones from aggregative clutters in FSL.

Few-Shot Learning

Data-Driven Short-Term Voltage Stability Assessment Based on Spatial-Temporal Graph Convolutional Network

no code implementations5 Mar 2021 Yonghong Luo, Chao Lu, Lipeng Zhu, Jie Song

The proposed STGCN utilizes graph convolution to integrate network topology information into the learning model to exploit spatial information.

Training Generative Adversarial Networks in One Stage

1 code implementation CVPR 2021 Chengchao Shen, Youtan Yin, Xinchao Wang, Xubin Li, Jie Song, Mingli Song

Based on the adversarial losses of the generator and discriminator, we categorize GANs into two classes, Symmetric GANs and Asymmetric GANs, and introduce a novel gradient decomposition method to unify the two, allowing us to train both classes in one stage and hence alleviate the training effort.

Data-free Knowledge Distillation Image Generation

Self-Born Wiring for Neural Trees

no code implementations ICCV 2021 Ying Chen, Feng Mao, Jie Song, Xinchao Wang, Huiqiong Wang, Mingli Song

Neural trees aim at integrating deep neural networks and decision trees so as to bring the best of the two worlds, including representation learning from the former and faster inference from the latter.

Representation Learning

Progressive Network Grafting for Few-Shot Knowledge Distillation

2 code implementations9 Dec 2020 Chengchao Shen, Xinchao Wang, Youtan Yin, Jie Song, Sihui Luo, Mingli Song

In this paper, we investigate the practical few-shot knowledge distillation scenario, where we assume only a few samples without human annotations are available for each category.

Knowledge Distillation Model Compression +1

Convolutional Autoencoders for Human Motion Infilling

1 code implementation22 Oct 2020 Manuel Kaufmann, Emre Aksan, Jie Song, Fabrizio Pece, Remo Ziegler, Otmar Hilliges

At the heart of our approach lies the idea to cast motion infilling as an inpainting problem and to train a convolutional de-noising autoencoder on image-like representations of motion sequences.

Category Level Object Pose Estimation via Neural Analysis-by-Synthesis

no code implementations ECCV 2020 Xu Chen, Zijian Dong, Jie Song, Andreas Geiger, Otmar Hilliges

Many object pose estimation algorithms rely on the analysis-by-synthesis framework which requires explicit representations of individual object instances.

Image Generation Object +1

Sparse Coding Driven Deep Decision Tree Ensembles for Nuclear Segmentation in Digital Pathology Images

no code implementations13 Aug 2020 Jie Song, Liang Xiao, Mohsen Molaei, Zhichao Lian

In this way, rich image appearance models together with more contextual information are integrated by learning a series of decision tree ensembles.

Image Segmentation Nuclear Segmentation +2

Impression Space from Deep Template Network

no code implementations10 Jul 2020 Gongfan Fang, Xinchao Wang, Haofei Zhang, Jie Song, Mingli Song

This network is referred to as the {\emph{Template Network}} because its filters will be used as templates to reconstruct images from the impression.

Image Generation Translation

DEPARA: Deep Attribution Graph for Deep Knowledge Transferability

1 code implementation CVPR 2020 Jie Song, Yixin Chen, Jingwen Ye, Xinchao Wang, Chengchao Shen, Feng Mao, Mingli Song

In this paper, we propose the DEeP Attribution gRAph (DEPARA) to investigate the transferability of knowledge learned from PR-DNNs.

Model Selection Transfer Learning

Data-Free Adversarial Distillation

3 code implementations23 Dec 2019 Gongfan Fang, Jie Song, Chengchao Shen, Xinchao Wang, Da Chen, Mingli Song

Knowledge Distillation (KD) has made remarkable progress in the last few years and become a popular paradigm for model compression and knowledge transfer.

Knowledge Distillation Model Compression +2

Deep Model Transferability from Attribution Maps

2 code implementations NeurIPS 2019 Jie Song, Yixin Chen, Xinchao Wang, Chengchao Shen, Mingli Song

Exploring the transferability between heterogeneous tasks sheds light on their intrinsic interconnections, and consequently enables knowledge transfer from one task to another so as to reduce the training effort of the latter.

Transfer Learning

Investigation of wind pressures on tall building under interference effects using machine learning techniques

no code implementations20 Aug 2019 Gang Hu, Lingbo Liu, DaCheng Tao, Jie Song, K. C. S. Kwok

This study used machine learning techniques to resolve the conflicting requirement between limited wind tunnel tests that produce unreliable results and a completed investigation of the interference effects that is costly and time-consuming.

BIG-bench Machine Learning

Customizing Student Networks From Heterogeneous Teachers via Adaptive Knowledge Amalgamation

2 code implementations ICCV 2019 Chengchao Shen, Mengqi Xue, Xinchao Wang, Jie Song, Li Sun, Mingli Song

To this end, we introduce a dual-step strategy that first extracts the task-specific knowledge from the heterogeneous teachers sharing the same sub-task, and then amalgamates the extracted knowledge to build the student network.

Unpaired Pose Guided Human Image Generation

1 code implementation8 Jan 2019 Xu Chen, Jie Song, Otmar Hilliges

This paper studies the task of full generative modelling of realistic images of humans, guided only by coarse sketch of the pose, while providing control over the specific instance or type of outfit worn by the user.

Image-to-Image Translation Translation

Monocular Neural Image Based Rendering with Continuous View Control

2 code implementations ICCV 2019 Xu Chen, Jie Song, Otmar Hilliges

The approach is self-supervised and only requires 2D images and associated view transforms for training.

Novel View Synthesis

End-to-end Learning for Graph Decomposition

no code implementations ICCV 2019 Jie Song, Bjoern Andres, Michael Black, Otmar Hilliges, Siyu Tang

The new optimization problem can be viewed as a Conditional Random Field (CRF) in which the random variables are associated with the binary edge labels of the initial graph and the hard constraints are introduced in the CRF as high-order potentials.

Clustering Multi-Person Pose Estimation

Amalgamating Knowledge towards Comprehensive Classification

1 code implementation7 Nov 2018 Chengchao Shen, Xinchao Wang, Jie Song, Li Sun, Mingli Song

We propose in this paper to study a new model-reusing task, which we term as \emph{knowledge amalgamation}.

Classification General Classification

Selective Zero-Shot Classification with Augmented Attributes

no code implementations ECCV 2018 Jie Song, Chengchao Shen, Jie Lei, An-Xiang Zeng, Kairi Ou, DaCheng Tao, Mingli Song

We propose a selective zero-shot classifier based on both the human defined and the automatically discovered residual attributes.

Attribute Classification +2

Transductive Unbiased Embedding for Zero-Shot Learning

no code implementations CVPR 2018 Jie Song, Chengchao Shen, Yezhou Yang, Yang Liu, Mingli Song

Most existing Zero-Shot Learning (ZSL) methods have the strong bias problem, in which instances of unseen (target) classes tend to be categorized as one of the seen (source) classes.

Transductive Learning Zero-Shot Learning

Cross-modal Deep Variational Hand Pose Estimation

1 code implementation CVPR 2018 Adrian Spurr, Jie Song, Seonwook Park, Otmar Hilliges

Furthermore, we show that our proposed method can be used without changes on depth images and performs comparably to specialized methods.

Hand Pose Estimation

Learning Human Motion Models for Long-term Predictions

no code implementations10 Apr 2017 Partha Ghosh, Jie Song, Emre Aksan, Otmar Hilliges

Furthermore, we propose new evaluation protocols to assess the quality of synthetic motion sequences even for which no ground truth data exists.

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