The field of video and language modeling is rapidly advancing, with a focus on improving efficiency and reducing computational costs. Recent developments have led to the creation of novel attention mechanisms, such as periodic sparse Transformers, that enable efficient long-context modeling. Additionally, advancements in diffusion-based models have resulted in faster and more accurate video generation and reconstruction methods. Noteworthy papers in this area include: Pi-Attention, which achieves state-of-the-art results in language modeling and retrieval tasks with reduced computational costs. LiteAttention, which accelerates diffusion Transformers in video generation by exploiting temporal coherence in attention patterns. Other notable works, such as SOTFormer, ProAV-DiT, and TempoMaster, have also made significant contributions to the field of video object detection, audio-video generation, and long video generation, respectively.
Advances in Efficient Video and Language Modeling
Sources
$\pi$-Attention: Periodic Sparse Transformers for Efficient Long-Context Modeling
LiteAttention: A Temporal Sparse Attention for Diffusion Transformers
SOTFormer: A Minimal Transformer for Unified Object Tracking and Trajectory Prediction
Phase-Coded Memory and Morphological Resonance: A Next-Generation Retrieval-Augmented Generator Architecture
PipeDiT: Accelerating Diffusion Transformers in Video Generation with Task Pipelining and Model Decoupling
ProAV-DiT: A Projected Latent Diffusion Transformer for Efficient Synchronized Audio-Video Generation
TIMERIPPLE: Accelerating vDiTs by Understanding the Spatio-Temporal Correlations in Latent Space
Null-Space Diffusion Distillation for Efficient Photorealistic Lensless Imaging
TempoMaster: Efficient Long Video Generation via Next-Frame-Rate Prediction
Recurrent Autoregressive Diffusion: Global Memory Meets Local Attention
FoleyBench: A Benchmark For Video-to-Audio Models
Temporal Object-Aware Vision Transformer for Few-Shot Video Object Detection
InstantViR: Real-Time Video Inverse Problem Solver with Distilled Diffusion Prior
FlowRoI A Fast Optical Flow Driven Region of Interest Extraction Framework for High-Throughput Image Compression in Immune Cell Migration Analysis
FreeSwim: Revisiting Sliding-Window Attention Mechanisms for Training-Free Ultra-High-Resolution Video Generation
First Frame Is the Place to Go for Video Content Customization
Decoupling Complexity from Scale in Latent Diffusion Model
VTinker: Guided Flow Upsampling and Texture Mapping for High-Resolution Video Frame Interpolation
Flow and Depth Assisted Video Prediction with Latent Transformer
Investigating Optical Flow Computation: From Local Methods to a Multiresolution Horn-Schunck Implementation with Bilinear Interpolation