activity
20212026
most citedDomain Adaptation on Point Clouds via Geometry-Aware Implicits

65 citations · 80 across the 13 of their papers we have counts for

collaborators

13 papers

cs.RO2026

Geometry-Aware Motion Latents for Learning Robust Manipulation Policies

Yunchao Zhang, Yijia Weng, Ruizhe Liu +3

Learning motion latents for robotic manipulation heavily relies on extracting motion patterns from visual sequences, yet effective action abstractions require understanding three-d…

cs.CV2024★ 1 cited

InfoGaussian: Structure-Aware Dynamic Gaussians through Lightweight Information Shaping

Yunchao Zhang, Guandao Yang, Leonidas Guibas +1

3D Gaussians, as a low-level scene representation, typically involve thousands to millions of Gaussians. This makes it difficult to control the scene in ways that reflect the under…

cs.CV2023

Towards Learning Geometric Eigen-Lengths Crucial for Fitting Tasks

Yijia Weng, Kaichun Mo, Ruoxi Shi +2

Some extremely low-dimensional yet crucial geometric eigen-lengths often determine the success of some geometric tasks. For example, the height of an object is important to measure…

cs.CV2023★ 1 cited

JacobiNeRF: NeRF Shaping with Mutual Information Gradients

Xiaomeng Xu, Yanchao Yang, Kaichun Mo +3

We propose a method that trains a neural radiance field (NeRF) to encode not only the appearance of the scene but also semantic correlations between scene points, regions, or entit…

cs.CV2022

COPILOT: Human-Environment Collision Prediction and Localization from Egocentric Videos

Boxiao Pan, Bokui Shen, Davis Rempe +4

The ability to forecast human-environment collisions from egocentric observations is vital to enable collision avoidance in applications such as VR, AR, and wearable assistive robo…

cs.CV2022★ 2 cited

6D Camera Relocalization in Visually Ambiguous Extreme Environments

Yang Zheng, Tolga Birdal, Fei Xia +3

We propose a novel method to reliably estimate the pose of a camera given a sequence of images acquired in extreme environments such as deep seas or extraterrestrial terrains. Data…

cs.CV2022

SpOT: Spatiotemporal Modeling for 3D Object Tracking

Colton Stearns, Davis Rempe, Jie Li +5

3D multi-object tracking aims to uniquely and consistently identify all mobile entities through time. Despite the rich spatiotemporal information available in this setting, current…

cs.CV2022★ 2 cited

GIMO: Gaze-Informed Human Motion Prediction in Context

Yang Zheng, Yanchao Yang, Kaichun Mo +5

Predicting human motion is critical for assistive robots and AR/VR applications, where the interaction with humans needs to be safe and comfortable. Meanwhile, an accurate predicti…

cs.CV2021★ 65 cited

Domain Adaptation on Point Clouds via Geometry-Aware Implicits

Yuefan Shen, Yanchao Yang, Mi Yan +3

As a popular geometric representation, point clouds have attracted much attention in 3D vision, leading to many applications in autonomous driving and robotics. One important yet u…

cs.CV2021

Object Pursuit: Building a Space of Objects via Discriminative Weight Generation

Chuanyu Pan, Yanchao Yang, Kaichun Mo +2

We propose a framework to continuously learn object-centric representations for visual learning and understanding. Existing object-centric representations either rely on supervisio…

cs.CV2021★ 2 cited

IFR-Explore: Learning Inter-object Functional Relationships in 3D Indoor Scenes

Qi Li, Kaichun Mo, Yanchao Yang +2

Building embodied intelligent agents that can interact with 3D indoor environments has received increasing research attention in recent years. While most works focus on single-obje…

cs.CV2021

ADeLA: Automatic Dense Labeling with Attention for Viewpoint Adaptation in Semantic Segmentation

Yanchao Yang, Hanxiang Ren, He Wang +5

We describe an unsupervised domain adaptation method for image content shift caused by viewpoint changes for a semantic segmentation task. Most existing methods perform domain alig…

cs.CV2021★ 7 cited

DCL: Differential Contrastive Learning for Geometry-Aware Depth Synthesis

Yuefan Shen, Yanchao Yang, Youyi Zheng +2

We describe a method for unpaired realistic depth synthesis that learns diverse variations from the real-world depth scans and ensures geometric consistency between the synthetic a…