activity
20222026
most citedImperative Learning: A Self-supervised Neuro-Symbolic Learning Framework for Robot Autonomy

12 citations · 17 across the 10 of their papers we have counts for

collaborators

11 papers

cs.RO2026

Point-Level Refinable Semantic Mapping for Spatial Understanding

Taimeng Fu, Yi Du, Zitong Zhan +4

Open-vocabulary 3D semantic maps have emerged as a key spatial memory representation for long-horizon robot autonomy, enabling robots to reason about objects, their spatial relatio…

cs.RO2026

Neuro-Symbolic Learning for Long-Horizon Task Planning Under Complex Logical Constraints

Qiwei Du, Zitong Zhan, Shaoshu Su +7

Task planning often suffers from severe efficiency bottlenecks when robots must reason over long-horizon action sequences under complex logical constraints, including object afford…

cs.LG2026

Data Warmup: Complexity-Aware Curricula for Efficient Diffusion Training

Jinhong Lin, Pan Wang, Zitong Zhan +2

A key inefficiency in diffusion training occurs when a randomly initialized network, lacking visual priors, encounters gradients from the full complexity spectrum--most of which it…

cs.CV2025

InstantSfM: Towards GPU-Native SfM for the Deep Learning Era

Jiankun Zhong, Zitong Zhan, Quankai Gao +6

Structure-from-Motion (SfM) is a fundamental technique for recovering camera poses and scene structure from multi-view imagery, serving as a critical upstream component for applica…

cs.RO2025

Fast Task Planning with Neuro-Symbolic Relaxation

Qiwei Du, Bowen Li, Yi Du +5

Real-world task planning requires long-horizon reasoning over large sets of objects with complex relationships and attributes, leading to a combinatorial explosion for classical sy…

cs.RO2025★ 2 cited

AnyNav: Visual Neuro-Symbolic Friction Learning for Off-road Navigation

Taimeng Fu, Zitong Zhan, Zhipeng Zhao +7

Off-road navigation is critical for a wide range of field robotics applications from planetary exploration to disaster response. However, it remains a longstanding challenge due to…

cs.RO2024

Bundle Adjustment in the Eager Mode

Zitong Zhan, Huan Xu, Zihang Fang +3

Bundle adjustment (BA) is a critical technique in various robotic applications such as simultaneous localization and mapping (SLAM), augmented reality (AR), and photogrammetry. BA…

cs.RO2024★ 12 cited

Imperative Learning: A Self-supervised Neuro-Symbolic Learning Framework for Robot Autonomy

Chen Wang, Kaiyi Ji, Junyi Geng +16

Data-driven methods such as reinforcement and imitation learning have achieved remarkable success in robot autonomy. However, their data-centric nature still hinders them from gene…

cs.RO2023

PyPose v0.6: The Imperative Programming Interface for Robotics

Zitong Zhan, Xiangfu Li, Qihang Li +33

PyPose is an open-source library for robot learning. It combines a learning-based approach with physics-based optimization, which enables seamless end-to-end robot learning. It has…

cs.CV2022★ 1 cited

Robust Online Video Instance Segmentation with Track Queries

Zitong Zhan, Daniel McKee, Svetlana Lazebnik

Recently, transformer-based methods have achieved impressive results on Video Instance Segmentation (VIS). However, most of these top-performing methods run in an offline manner by…

cs.CV2022★ 2 cited

Transfer of Representations to Video Label Propagation: Implementation Factors Matter

Daniel McKee, Zitong Zhan, Bing Shuai +3

This work studies feature representations for dense label propagation in video, with a focus on recently proposed methods that learn video correspondence using self-supervised sign…