12 citations · 21 across the 19 of their papers we have counts for
19 papers
Diffusion-aided Extreme Video Compression with Lightweight Semantics Guidance
Maojun Zhang, Haotian Wu, Richeng Jin +2
Modern video codecs and learning-based approaches struggle for semantic reconstruction at extremely low bit-rates due to reliance on low-level spatiotemporal redundancies. Generati…
Leveraging Overfitting for Low-Complexity and Modality-Agnostic Joint Source-Channel Coding
Haotian Wu, Gen Li, Pier Luigi Dragotti +1
This paper introduces Implicit-JSCC, a novel overfitted joint source-channel coding paradigm that directly optimizes channel symbols and a lightweight neural decoder for each sourc…
CNNs in the Air via Reconfigurable Intelligent Surfaces
Meng Hua, Haotian Wu, Deniz Gündüz
This paper introduces AirCNN, a novel paradigm for implementing convolutional neural networks (CNNs) via over-the-air (OTA) analog computation. By leveraging multiple reconfigurabl…
Compression Beyond Pixels: Semantic Compression with Multimodal Foundation Models
Ruiqi Shen, Haotian Wu, Wenjing Zhang +2
Recent deep learning-based methods for lossy image compression achieve competitive rate-distortion performance through extensive end-to-end training and advanced architectures. How…
Implementing Neural Networks Over-the-Air via Reconfigurable Intelligent Surfaces
Meng Hua, Chenghong Bian, Haotian Wu +1
In this paper, we investigate reconfigurable intelligent surface (RIS)-aided multiple-input-multiple-output (MIMO) OAC systems designed to emulate the fully-connected (FC) layer of…
LotteryCodec: Searching the Implicit Representation in a Random Network for Low-Complexity Image Compression
Haotian Wu, Gongpu Chen, Pier Luigi Dragotti +1
We introduce and validate the lottery codec hypothesis, which states that untrained subnetworks within randomly initialized networks can serve as synthesis networks for overfitted…
Realizing Fully-Connected Layers Over the Air via Reconfigurable Intelligent Surfaces
Meng Hua, Chenghong Bian, Haotian Wu +1
By leveraging the waveform superposition property of the multiple access channel, over-the-air computation (AirComp) enables the execution of digital computations through analog me…
Zero-Shot Semantic Communication with Multimodal Foundation Models
Jiangjing Hu, Haotian Wu, Wenjing Zhang +4
Most existing semantic communication (SemCom) systems use deep joint source-channel coding (DeepJSCC) to encode task-specific semantics in a goal-oriented manner. However, their re…
Actions Speak Louder Than Words: Rate-Reward Trade-off in Markov Decision Processes
Haotian Wu, Gongpu Chen, Deniz Gündüz
The impact of communication on decision-making systems has been extensively studied under the assumption of dedicated communication channels. We instead consider communicating thro…
Semantics-Guided Diffusion for Deep Joint Source-Channel Coding in Wireless Image Transmission
Maojun Zhang, Haotian Wu, Guangxu Zhu +3
Joint source-channel coding (JSCC) offers a promising avenue for enhancing transmission efficiency by jointly incorporating source and channel statistics into the system design. A…
DiffCP: Ultra-Low Bit Collaborative Perception via Diffusion Model
Ruiqing Mao, Haotian Wu, Yukuan Jia +5
Collaborative perception (CP) is emerging as a promising solution to the inherent limitations of stand-alone intelligence. However, current wireless communication systems are unabl…
MIMO Channel as a Neural Function: Implicit Neural Representations for Extreme CSI Compression in Massive MIMO Systems
Haotian Wu, Maojun Zhang, Yulin Shao +2
Acquiring and utilizing accurate channel state information (CSI) can significantly improve transmission performance, thereby holding a crucial role in realizing the potential advan…
Process-and-Forward: Deep Joint Source-Channel Coding Over Cooperative Relay Networks
Chenghong Bian, Yulin Shao, Haotian Wu +2
We introduce deep joint source-channel coding (DeepJSCC) schemes for image transmission over cooperative relay channels. The relay either amplifies-and-forwards its received signal…
Deep Joint Source-Channel Coding for Adaptive Image Transmission over MIMO Channels
Haotian Wu, Yulin Shao, Chenghong Bian +2
This paper introduces a vision transformer (ViT)-based deep joint source and channel coding (DeepJSCC) scheme for wireless image transmission over multiple-input multiple-output (M…
Transformer-aided Wireless Image Transmission with Channel Feedback
Haotian Wu, Yulin Shao, Emre Ozfatura +2
This paper presents a novel wireless image transmission paradigm that can exploit feedback from the receiver, called DeepJSCC-ViT-f. We consider a block feedback channel model, whe…
Features-over-the-Air: Contrastive Learning Enabled Cooperative Edge Inference
Haotian Wu, Nitish Mital, Krystian Mikolajczyk +1
We study the collaborative image retrieval problem at the wireless edge, where multiple edge devices capture images of the same object, which are then used jointly to retrieve simi…
Collaborative Semantic Communication for Edge Inference
Wing Fei Lo, Nitish Mital, Haotian Wu +1
We study the collaborative image retrieval problem at the wireless edge, where multiple edge devices capture images of the same object from different angles and locations, which ar…
Deep Joint Source-Channel Coding Over Cooperative Relay Networks
Chenghong Bian, Yulin Shao, Haotian Wu +1
This paper presents a novel deep joint source-channel coding (DeepJSCC) scheme for image transmission over a half-duplex cooperative relay channel. Specifically, we apply DeepJSCC…
Space-time design for deep joint source channel coding of images Over MIMO channels
Chenghong Bian, Yulin Shao, Haotian Wu +1
We propose novel deep joint source-channel coding (DeepJSCC) algorithms for wireless image transmission over multi-input multi-output (MIMO) Rayleigh fading channels, when channel…