Live video streaming has grown dramatically in recent years. A key challenge is achieving high video quality of experience (QoE) in low-rate networks. To tackle this problem, recent streaming approaches strategically drop video frames, thus reducing the bandwidth required. However, these methods are usually designed for video on demand (VoD) services and perform poorly in live video streaming. In this paper, we design a new live video streaming approach, Reparo, which aims to improve users' QoE in low-rate networks. On the upload client side, Reparo discards video frames such that they are never encoded or transmitted. To decide which frames should be dropped, we design a real-time Video Frame Discarding (VFD) model, which strives to minimize the impact on video quality while maximizing bandwidth savings. To complement this, Reparo further proposes a modified adaptive bitrate algorithm and two encoding modes, targeting low-frame-rate encoding. On the server side, Reparo then recovers the dropped frames using a lightweight Video Frame Interpolation Deep Neural Network (VFI-DNN). Experimental results show that, compared with vanilla DASH, Reparo reaches an SSIM gain of 0.018, or reduces bandwidth consumption by 30.86%. With an average bandwidth of 0.974Mbps, it improves QoE by 18.13% on average compared to DASH.

The user experience of mobile web video streaming is often impacted by insufficient and dynamic network bandwidth. In this paper, we design Bidirectionally Optimized Super-Resolution (BiSR) to improve the quality of experience (QoE) for mobile web users under limited bandwidth. BiSR exploits a deep neural network (DNN)-based model to super-resolve key frames efficiently without changing the inter-frame spatial-temporal information. We then propose a downscaling DNN and a mobile-specific optimized lightweight super-resolution DNN to enhance the performance. Finally, a novel reinforcement learning-based adaptive bitrate (ABR) algorithm is proposed to verify the performance of BiSR on real network traces. Our evaluation, using a full system implementation, shows that BiSR saves 26% of bitrate compared to the traditional H.264 codec and improves the SSIM of video by 3.7% compared to the prior state-of-the-art. Overall, BiSR enhances the user-perceived quality of experience by up to 30.6%.