Search Results for author:
Found 9 papers, 7 papers with code
Sim-to-Real Transfer via 3D Feature Fields for Vision-and-Language Navigation
Vision-and-language navigation (VLN) enables the agent to navigate to a remote location in 3D environments following the natural language instruction.
MoFormer: Multi-objective Antimicrobial Peptide Generation Based on Conditional Transformer Joint Multi-modal Fusion Descriptor
Deep learning holds a big promise for optimizing existing peptides with more desirable properties, a critical step towards accelerating new drug discovery.
Lookahead Exploration with Neural Radiance Representation for Continuous Vision-Language Navigation
Vision-and-language navigation (VLN) enables the agent to navigate to a remote location following the natural language instruction in 3D environments.
Detecting Machine-Generated Texts by Multi-Population Aware Optimization for Maximum Mean Discrepancy
Unfortunately, it is challenging to distinguish MGTs and human-written texts because the distributional discrepancy between them is often very subtle due to the remarkable performance of LLMs.
GridMM: Grid Memory Map for Vision-and-Language Navigation
Vision-and-language navigation (VLN) enables the agent to navigate to a remote location following the natural language instruction in 3D environments.
Vision-Based Fruit Recognition via Multi-Scale Attention CNN
Fruit quality assessment, grading and sorting are of vital importance to fruit processing, and all these involve fruit recognition.
Robust Category-Level 3D Pose Estimation from Synthetic Data
In this work, we aim to narrow the performance gap between models trained on synthetic data and few real images and fully supervised models trained on large-scale data.
Detecting Adversarial Data by Probing Multiple Perturbations Using Expected Perturbation Score
Last, we propose an EPS-based adversarial detection (EPS-AD) method, in which we develop EPS-based maximum mean discrepancy (MMD) as a metric to measure the discrepancy between the test sample and natural samples.
KERM: Knowledge Enhanced Reasoning for Vision-and-Language Navigation
The proposed KERM can automatically select and gather crucial and relevant cues, obtaining more accurate action prediction.
