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04/28/2023
NeRF-LiDAR: Generating Realistic LiDAR Point Clouds with Neural Radiance Fields
Labeling LiDAR point clouds for training autonomous driving is extremely...
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03/01/2023
S-NeRF: Neural Radiance Fields for Street Views
Neural Radiance Fields (NeRFs) aim to synthesize novel views of objects ...
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02/23/2023
Improved Training of Mixture-of-Experts Language GANs
Despite the dramatic success in image generation, Generative Adversarial...
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01/16/2023
PECAN: Leveraging Policy Ensemble for Context-Aware Zero-Shot Human-AI Coordination
Zero-shot human-AI coordination holds the promise of collaborating with ...
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12/30/2022
Transformer in Transformer as Backbone for Deep Reinforcement Learning
Designing better deep networks and better reinforcement learning (RL) al...
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11/18/2022
Delving into Transformer for Incremental Semantic Segmentation
Incremental semantic segmentation(ISS) is an emerging task where old mod...
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07/05/2022
Softmax-free Linear Transformers
Vision transformers (ViTs) have pushed the state-of-the-art for various ...
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06/02/2022
RACA: Relation-Aware Credit Assignment for Ad-Hoc Cooperation in Multi-Agent Deep Reinforcement Learning
In recent years, reinforcement learning has faced several challenges in ...
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01/27/2022
DecisionHoldem: Safe Depth-Limited Solving With Diverse Opponents for Imperfect-Information Games
An imperfect-information game is a type of game with asymmetric informat...
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12/07/2021
The Partially Observable Asynchronous Multi-Agent Cooperation Challenge
Multi-agent reinforcement learning (MARL) has received increasing attent...
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11/07/2021
Coordinated Proximal Policy Optimization
We present Coordinated Proximal Policy Optimization (CoPPO), an algorith...
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10/22/2021
SOFT: Softmax-free Transformer with Linear Complexity
Vision transformers (ViTs) have pushed the state-of-the-art for various ...
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04/09/2021
Learning to Reweight Imaginary Transitions for Model-Based Reinforcement Learning
Model-based reinforcement learning (RL) is more sample efficient than mo...
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10/24/2020
Planning with Exploration: Addressing Dynamics Bottleneck in Model-based Reinforcement Learning
Model-based reinforcement learning is a framework in which an agent lear...
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09/10/2019
MVP-Net: Multi-view FPN with Position-aware Attention for Deep Universal Lesion Detection
Universal lesion detection (ULD) on computed tomography (CT) images is a...
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08/06/2019
Point Cloud Super Resolution with Adversarial Residual Graph Networks
Point cloud super-resolution is a fundamental problem for 3D reconstruct...
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04/16/2019
SparseMask: Differentiable Connectivity Learning for Dense Image Prediction
In this paper, we aim at automatically searching an efficient network ar...
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03/28/2019
FastFCN: Rethinking Dilated Convolution in the Backbone for Semantic Segmentation
Modern approaches for semantic segmentation usually employ dilated convo...
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01/06/2019
Transductive Zero-Shot Learning with Visual Structure Constraint
Zero-shot Learning (ZSL) aims to recognize objects of the unseen classes...
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03/18/2018
Discriminative Learning of Latent Features for Zero-Shot Recognition
Zero-shot learning (ZSL) aims to recognize unseen image categories by le...
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03/15/2018
Fast End-to-End Trainable Guided Filter
Image processing and pixel-wise dense prediction have been advanced by h...
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02/27/2018
Mixed Supervised Object Detection with Robust Objectness Transfer
In this paper, we consider the problem of leveraging existing fully labe...
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10/09/2017
MSC: A Dataset for Macro-Management in StarCraft II
Macro-management is an important problem in StarCraft, which has been st...
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09/14/2017
A2-RL: Aesthetics Aware Reinforcement Learning for Image Cropping
Image cropping aims at improving the aesthetic quality of images by adju...
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03/21/2017
