Search Results for author: Yuejiang Liu

Found 10 papers, 8 papers with code

Co-Supervised Learning: Improving Weak-to-Strong Generalization with Hierarchical Mixture of Experts

no code implementations23 Feb 2024 Yuejiang Liu, Alexandre Alahi

Steering the behavior of a strong model pre-trained on internet-scale data can be difficult due to the scarcity of competent supervisors.

Sim-to-Real Causal Transfer: A Metric Learning Approach to Causally-Aware Interaction Representations

no code implementations7 Dec 2023 Yuejiang Liu, Ahmad Rahimi, Po-Chien Luan, Frano Rajič, Alexandre Alahi

Modeling spatial-temporal interactions among neighboring agents is at the heart of multi-agent problems such as motion forecasting and crowd navigation.

Metric Learning Motion Forecasting +1

On Pitfalls of Test-Time Adaptation

1 code implementation6 Jun 2023 Hao Zhao, Yuejiang Liu, Alexandre Alahi, Tao Lin

Test-Time Adaptation (TTA) has recently emerged as a promising approach for tackling the robustness challenge under distribution shifts.

Model Selection Test-time Adaptation

Motion Style Transfer: Modular Low-Rank Adaptation for Deep Motion Forecasting

1 code implementation6 Nov 2022 Parth Kothari, Danya Li, Yuejiang Liu, Alexandre Alahi

To this end, we introduce two components that exploit our prior knowledge of motion style shifts: (i) a low-rank motion style adapter that projects and adjusts the style features at a low-dimensional bottleneck; and (ii) a modular adapter strategy that disentangles the features of scene context and motion history to facilitate a fine-grained choice of adaptation layers.

Motion Forecasting Motion Style Transfer +2

TTT++: When Does Self-Supervised Test-Time Training Fail or Thrive?

1 code implementation NeurIPS 2021 Yuejiang Liu, Parth Kothari, Bastien Van Delft, Baptiste Bellot-Gurlet, Taylor Mordan, Alexandre Alahi

In this work, we first provide an in-depth look at its limitations and show that TTT can possibly deteriorate, instead of improving, the test-time performance in the presence of severe distribution shifts.

Contrastive Learning Self-Supervised Learning

Social NCE: Contrastive Learning of Socially-aware Motion Representations

4 code implementations ICCV 2021 Yuejiang Liu, Qi Yan, Alexandre Alahi

Learning socially-aware motion representations is at the core of recent advances in multi-agent problems, such as human motion forecasting and robot navigation in crowds.

Autonomous Navigation Motion Forecasting +1

Collaborative Sampling in Generative Adversarial Networks

1 code implementation2 Feb 2019 Yuejiang Liu, Parth Kothari, Alexandre Alahi

The standard practice in Generative Adversarial Networks (GANs) discards the discriminator during sampling.

Image Generation

Crowd-Robot Interaction: Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learning

6 code implementations24 Sep 2018 Changan Chen, Yuejiang Liu, Sven Kreiss, Alexandre Alahi

We propose to (i) rethink pairwise interactions with a self-attention mechanism, and (ii) jointly model Human-Robot as well as Human-Human interactions in the deep reinforcement learning framework.

Human Dynamics Navigate +3

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