most cited3D Part Assembly Generation with Instance Encoded Transformer

21 citations · 25 across the 6 of their papers we have counts for

collaborators

6 papers

cs.RO20231 cited

InViG: Benchmarking Interactive Visual Grounding with 500K Human-Robot Interactions

Hanbo Zhang, Jie Xu, Yuchen Mo +1

Ambiguity is ubiquitous in human communication. Previous approaches in Human-Robot Interaction (HRI) have often relied on predefined interaction templates, leading to reduced perfo…

cs.RO20231 cited

Exploring Visual Pre-training for Robot Manipulation: Datasets, Models and Methods

Ya Jing, Xuelin Zhu, Xingbin Liu +4

Visual pre-training with large-scale real-world data has made great progress in recent years, showing great potential in robot learning with pixel observations. However, the recipe…

cs.CV20231 cited

What Matters in Training a GPT4-Style Language Model with Multimodal Inputs?

Yan Zeng, Hanbo Zhang, Jiani Zheng +5

Recent advancements in Large Language Models (LLMs) such as GPT4 have displayed exceptional multi-modal capabilities in following open-ended instructions given images. However, the…

cs.CV2023

ClickSeg: 3D Instance Segmentation with Click-Level Weak Annotations

Leyao Liu, Tao Kong, Minzhao Zhu +2

3D instance segmentation methods often require fully-annotated dense labels for training, which are costly to obtain. In this paper, we present ClickSeg, a novel click-level weakly…

cs.RO20231 cited

Learning to Explore Informative Trajectories and Samples for Embodied Perception

Ya Jing, Tao Kong

We are witnessing significant progress on perception models, specifically those trained on large-scale internet images. However, efficiently generalizing these perception models to…

cs.RO202221 cited

3D Part Assembly Generation with Instance Encoded Transformer

Rufeng Zhang, Tao Kong, Weihao Wang +2

It is desirable to enable robots capable of automatic assembly. Structural understanding of object parts plays a crucial role in this task yet remains relatively unexplored. In thi…