Search Results for author:
Found 28 papers, 11 papers with code
OmniCharacter: Towards Immersive Role-Playing Agents with Seamless Speech-Language Personality Interaction
Role-Playing Agents (RPAs), benefiting from large language models, is an emerging interactive AI system that simulates roles or characters with diverse personalities.
A Survey of 3D Reconstruction with Event Cameras: From Event-based Geometry to Neural 3D Rendering
Event cameras have emerged as promising sensors for 3D reconstruction due to their ability to capture per-pixel brightness changes asynchronously.
AccidentSim: Generating Physically Realistic Vehicle Collision Videos from Real-World Accident Reports
In this paper, we introduce AccidentSim, a novel framework that generates physically realistic vehicle collision videos by extracting and utilizing the physical clues and contextual information available in real-world vehicle accident reports.
A Survey on Event-driven 3D Reconstruction: Development under Different Categories
Event cameras have gained increasing attention for 3D reconstruction due to their high temporal resolution, low latency, and high dynamic range.
EvAnimate: Event-conditioned Image-to-Video Generation for Human Animation
In this paper, we propose EvAnimate, the first method leveraging event streams as robust and precise motion cues for conditional human image animation.
Adaptive Backdoor Attacks with Reasonable Constraints on Graph Neural Networks
To tackle the above issues, we propose ABARC, the first Adaptive Backdoor Attack with Reasonable Constraints, applying to both graph-level and node-level tasks in GNNs.
LLM-EvRep: Learning an LLM-Compatible Event Representation Using a Self-Supervised Framework
Recent advancements in event-based recognition have demonstrated significant promise, yet most existing approaches rely on extensive training, limiting their adaptability for efficient processing of event-driven visual content.
AutoCBT: An Autonomous Multi-agent Framework for Cognitive Behavioral Therapy in Psychological Counseling
Traditional in-person psychological counseling remains primarily niche, often chosen by individuals with psychological issues, while online automated counseling offers a potential solution for those hesitant to seek help due to feelings of shame.
NVS-SQA: Exploring Self-Supervised Quality Representation Learning for Neurally Synthesized Scenes without References
Neural View Synthesis (NVS), such as NeRF and 3D Gaussian Splatting, effectively creates photorealistic scenes from sparse viewpoints, typically evaluated by quality assessment methods like PSNR, SSIM, and LPIPS.
Towards End-to-End Neuromorphic Voxel-based 3D Object Reconstruction Without Physical Priors
Neuromorphic cameras, also known as event cameras, are asynchronous brightness-change sensors that can capture extremely fast motion without suffering from motion blur, making them particularly promising for 3D reconstruction in extreme environments.
Ranked #1 on
Single-View 3D Reconstruction
on SynthEVox3D-Tiny
AutoPatent: A Multi-Agent Framework for Automatic Patent Generation
As the capabilities of Large Language Models (LLMs) continue to advance, the field of patent processing has garnered increased attention within the natural language processing community.
Small Language Model as Data Prospector for Large Language Model
The quality of instruction data directly affects the performance of fine-tuned Large Language Models (LLMs).
NeRF-NQA: No-Reference Quality Assessment for Scenes Generated by NeRF and Neural View Synthesis Methods
To address the issues above, we propose NeRF-NQA, the first no-reference quality assessment method for densely-observed scenes synthesized from the NVS and NeRF variants.
Light Field Image Quality Assessment With Auxiliary Learning Based on Depthwise and Anglewise Separable Convolutions
Second, we further theoretically extend the LF-DSC to the angular space of LFI and introduce the novel concept of "light field anglewise separable convolution (LF-ASC)", which is capable of extracting both the spatial and angular features for comprehensive quality assessment with low complexity.
EvRepSL: Event-Stream Representation via Self-Supervised Learning for Event-Based Vision
However, most of the state-of-the-art event-stream representations are manually designed and the quality of these representations cannot be guaranteed due to the noisy nature of event-streams.
Beyond Gaussians: Fast and High-Fidelity 3D Splatting with Linear Kernels
Recent advancements in 3D Gaussian Splatting (3DGS) have substantially improved novel view synthesis, enabling high-quality reconstruction and real-time rendering.
Can Large Language Models Grasp Event Signals? Exploring Pure Zero-Shot Event-based Recognition
However, these methods heavily depend on extensive training and are inherently constrained by the characteristics of CLIP.
AgentCourt: Simulating Court with Adversarial Evolvable Lawyer Agents
Our core goal is to enable lawyer agents to learn how to argue a case, as well as improving their overall legal skills, through courtroom process simulation.
E2HQV: High-Quality Video Generation from Event Camera via Theory-Inspired Model-Aided Deep Learning
In this work, we propose \textbf{E2HQV}, a novel E2V paradigm designed to produce high-quality video frames from events.
Why are state-space models more expressive than $n$-gram models?
Recent advancements in recurrent neural networks (RNNs) have reinvigorated interest in their application to natural language processing tasks, particularly with the development of more efficient and parallelizable variants known as state space models (SSMs), which have shown competitive performance against transformer models while maintaining a lower memory footprint.
LFACon: Introducing Anglewise Attention to No-Reference Quality Assessment in Light Field Space
In this paper, we propose a novel concept of "anglewise attention" by introducing a multihead self-attention mechanism to the angular domain of an LFI.
Patents and intellectual property assets as non-fungible tokens: key technologies and challenges
The proposed framework provides fundamental elements and guidance for businesses in taking advantage of NFTs in real-world problems such as grant patents, funding, biotechnology, and so forth.
Towards Understanding Chinese Checkers with Heuristics, Monte Carlo Tree Search, and Deep Reinforcement Learning
The game of Chinese Checkers is a challenging traditional board game of perfect information that differs from other traditional games in two main aspects: first, unlike Chess, all checkers remain indefinitely in the game and hence the branching factor of the search tree does not decrease as the game progresses; second, unlike Go, there are also no upper bounds on the depth of the search tree since repetitions and backward movements are allowed.
NAIRS: A Neural Attentive Interpretable Recommendation System
In this paper, we develop a neural attentive interpretable recommendation system, named NAIRS.
Aspect and Sentiment Aware Abstractive Review Summarization
Review text has been widely studied in traditional tasks such as sentiment analysis and aspect extraction.
N-fold Superposition: Improving Neural Networks by Reducing the Noise in Feature Maps
Finally, we replicate this new block into n copies and concatenate them as the input to the FC layer.
GPSP: Graph Partition and Space Projection based Approach for Heterogeneous Network Embedding
Finally, we concatenate the projective vectors from bipartite subnetworks with the ones learned from homogeneous subnetworks to form the final representation of the heterogeneous network.
Generative Adversarial Network for Abstractive Text Summarization
In this paper, we propose an adversarial process for abstractive text summarization, in which we simultaneously train a generative model G and a discriminative model D. In particular, we build the generator G as an agent of reinforcement learning, which takes the raw text as input and predicts the abstractive summarization.
Ranked #5 on
Text Summarization
on CNN / Daily Mail (Anonymized)
Abstractive Text Summarization
Generative Adversarial Network
+3
