Search Results for author:
Found 21 papers, 7 papers with code
HUGS: Holistic Urban 3D Scene Understanding via Gaussian Splatting
Holistic understanding of urban scenes based on RGB images is a challenging yet important problem.
Safe Non-Stochastic Control of Control-Affine Systems: An Online Convex Optimization Approach
We study how to safely control nonlinear control-affine systems that are corrupted with bounded non-stochastic noise, i. e., noise that is unknown a priori and that is not necessarily governed by a stochastic model.
DreamLLM: Synergistic Multimodal Comprehension and Creation
This paper presents DreamLLM, a learning framework that first achieves versatile Multimodal Large Language Models (MLLMs) empowered with frequently overlooked synergy between multimodal comprehension and creation.
Ranked #1 on
Visual Question Answering
on MMBench
(GPT-3.5 score metric)
Safe Non-Stochastic Control of Linear Dynamical Systems
We study the problem of \textit{safe control of linear dynamical systems corrupted with non-stochastic noise}, and provide an algorithm that guarantees (i) zero constraint violation of convex time-varying constraints, and (ii) bounded dynamic regret, \ie bounded suboptimality against an optimal clairvoyant controller that knows the future noise a priori.
ChatSpot: Bootstrapping Multimodal LLMs via Precise Referring Instruction Tuning
Based on precise referring instruction, we propose ChatSpot, a unified end-to-end multimodal large language model that supports diverse forms of interactivity including mouse clicks, drag-and-drop, and drawing boxes, which provides a more flexible and seamless interactive experience.
GMM: Delving into Gradient Aware and Model Perceive Depth Mining for Monocular 3D Detection
In light of the success of sample mining techniques in 2D object detection, we propose a simple yet effective mining strategy for improving depth perception in 3D object detection.
Exploring Recurrent Long-term Temporal Fusion for Multi-view 3D Perception
In this paper, we explore an embarrassingly simple long-term recurrent fusion strategy built upon the LSS-based methods and find it already able to enjoy the merits from both sides, i. e., rich long-term information and efficient fusion pipeline.
A Comprehensive Survey on Multimodal Recommender Systems: Taxonomy, Evaluation, and Future Directions
Recommendation systems have become popular and effective tools to help users discover their interesting items by modeling the user preference and item property based on implicit interactions (e. g., purchasing and clicking).
Enhancing Dyadic Relations with Homogeneous Graphs for Multimodal Recommendation
On top of the finding, we propose a model that enhances the dyadic relations by learning Dual RepresentAtions of both users and items via constructing homogeneous Graphs for multimOdal recommeNdation.
Efficient Online Learning with Memory via Frank-Wolfe Optimization: Algorithms with Bounded Dynamic Regret and Applications to Control
In this paper, we enable projection-free online learning within the framework of Online Convex Optimization with Memory (OCO-M) -- OCO-M captures how the history of decisions affects the current outcome by allowing the online learning loss functions to depend on both current and past decisions.
MatrixVT: Efficient Multi-Camera to BEV Transformation for 3D Perception
This paper proposes an efficient multi-camera to Bird's-Eye-View (BEV) view transformation method for 3D perception, dubbed MatrixVT.
Ranked #2 on
Bird's-Eye View Semantic Segmentation
on nuScenes
(IoU lane - 224x480 - 100x100 at 0.5 metric)
Online Submodular Coordination with Bounded Tracking Regret: Theory, Algorithm, and Applications to Multi-Robot Coordination
We are motivated by the future of autonomy that involves multiple robots coordinating in dynamic, unstructured, and adversarial environments to complete complex tasks such as target tracking, environmental mapping, and area monitoring.
PersDet: Monocular 3D Detection in Perspective Bird's-Eye-View
To address this problem, we revisit the generation of BEV representation and propose detecting objects in perspective BEV -- a new BEV representation that does not require feature sampling.
Safe Control of Partially-Observed Linear Time-Varying Systems with Minimal Worst-Case Dynamic Regret
We present safe control of partially-observed linear time-varying systems in the presence of unknown and unpredictable process and measurement noise.
Bootstrap Latent Representations for Multi-modal Recommendation
Besides the user-item interaction graph, existing state-of-the-art methods usually use auxiliary graphs (e. g., user-user or item-item relation graph) to augment the learned representations of users and/or items.
Dense Teacher: Dense Pseudo-Labels for Semi-supervised Object Detection
To date, the most powerful semi-supervised object detectors (SS-OD) are based on pseudo-boxes, which need a sequence of post-processing with fine-tuned hyper-parameters.
Transformer for Polyp Detection
In recent years, as the Transformer has performed increasingly well on NLP tasks, many researchers have ported the Transformer structure to vision tasks , bridging the gap between NLP and CV tasks.
Grouptron: Dynamic Multi-Scale Graph Convolutional Networks for Group-Aware Dense Crowd Trajectory Forecasting
Accurate, long-term forecasting of pedestrian trajectories in highly dynamic and interactive scenes is a long-standing challenge.
RECIST-Net: Lesion detection via grouping keypoints on RECIST-based annotation
Universal lesion detection in computed tomography (CT) images is an important yet challenging task due to the large variations in lesion type, size, shape, and appearance.
A Guidance and Maneuvering Control System Design with Anti-collision Using Stream Functions with Vortex Flows for Autonomous Marine Vessels
Autonomous marine vessels are expected to avoid inter-vessel collisions and comply with the international regulations for safe voyages.
High-Performance FPGA-based Accelerator for Bayesian Neural Networks
Neural networks (NNs) have demonstrated their potential in a wide range of applications such as image recognition, decision making or recommendation systems.
