Search Results for author:
Found 18 papers, 12 papers with code
Urban Architect: Steerable 3D Urban Scene Generation with Layout Prior
(2) To handle the unbounded nature of urban scenes, we represent 3D scene with a Scalable Hash Grid structure, incrementally adapting to the growing scale of urban scenes.
LiDAR4D: Dynamic Neural Fields for Novel Space-time View LiDAR Synthesis
In light of this, we propose LiDAR4D, a differentiable LiDAR-only framework for novel space-time LiDAR view synthesis.
Pensieve: Retrospect-then-Compare Mitigates Visual Hallucination
Multi-modal Large Language Models (MLLMs) demonstrate remarkable success across various vision-language tasks.
GLC++: Source-Free Universal Domain Adaptation through Global-Local Clustering and Contrastive Affinity Learning
GLC++ enhances the novel category clustering accuracy of GLC by 4. 3% in open-set scenarios on Office-Home.
MAP: MAsk-Pruning for Source-Free Model Intellectual Property Protection
In this paper, we target a practical setting where only a well-trained source model is available and investigate how we can realize IP protection.
LEAD: Learning Decomposition for Source-free Universal Domain Adaptation
Besides, LEAD is also appealing in that it is complementary to most existing methods.
Ranked #1 on
Universal Domain Adaptation
on VisDA2017
Sophisticated Behavioral Simulation: A Possible Solution to Problems of Organized Complexity
As a matter of facts, they act as the best tool to handle problems in complex systems where closed-form expressions are unavailable and the target distribution in the representation space is too complex to be fully represented by data-driven learning models, such as deep learning (DL) models.
Spreeze: High-Throughput Parallel Reinforcement Learning Framework
While existing parallel RL frameworks encompass a variety of RL algorithms and parallelization techniques, the excessively burdensome communication frameworks hinder the attainment of the hardware's limit for final throughput and training effects on a single desktop.
CFBenchmark: Chinese Financial Assistant Benchmark for Large Language Model
Large language models (LLMs) have demonstrated great potential in the financial domain.
CFGPT: Chinese Financial Assistant with Large Language Model
The CFAPP is centered on large language models (LLMs) and augmented with additional modules to ensure multifaceted functionality in real-world application.
Urban Radiance Field Representation with Deformable Neural Mesh Primitives
To construct urban-level radiance fields efficiently, we design Deformable Neural Mesh Primitive~(DNMP), and propose to parameterize the entire scene with such primitives.
NeuralPCI: Spatio-temporal Neural Field for 3D Point Cloud Multi-frame Non-linear Interpolation
In light of these issues, we present NeuralPCI: an end-to-end 4D spatio-temporal Neural field for 3D Point Cloud Interpolation, which implicitly integrates multi-frame information to handle nonlinear large motions for both indoor and outdoor scenarios.
Ranked #1 on
3D Point Cloud Interpolation
on NL-Drive
UMC: A Unified Bandwidth-efficient and Multi-resolution based Collaborative Perception Framework
To verify our algorithm, we conducted experiments on the V2X-Sim and OPV2V datasets.
TMA: Temporal Motion Aggregation for Event-based Optical Flow
In this paper, we argue that temporal continuity is a vital element of event-based optical flow and propose a novel Temporal Motion Aggregation (TMA) approach to unlock its potential.
Modality-Agnostic Debiasing for Single Domain Generalization
We validate the superiority of our MAD in a variety of single-DG scenarios with different modalities, including recognition on 1D texts, 2D images, 3D point clouds, and semantic segmentation on 2D images.
Upcycling Models under Domain and Category Shift
We examine the superiority of our GLC on multiple benchmarks with different category shift scenarios, including partial-set, open-set, and open-partial-set DA.
Ranked #2 on
Universal Domain Adaptation
on VisDA2017
Unified Multimodal Model with Unlikelihood Training for Visual Dialog
Prior work performs the standard likelihood training for answer generation on the positive instances (involving correct answers).
Modeling and Analysis of Three Properties of Mobile Interactive Systems Based on Variable Petri Nets
The case study of a practical mobile payment system shows the effectiveness of the proposed method.
