TransVLM formalizes Shot Transition Detection as identifying full temporal transition segments rather than single cut points and introduces a VLM that injects optical flow as a motion prior via simple feature fusion, plus a synthetic data engine and benchmark.
Quo vadis, action recognition? a new model and the kinetics dataset
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A diffusion model for video generation extends image architectures with joint image-video training and improved conditional sampling, delivering first large-scale text-to-video results and state-of-the-art performance on video prediction and unconditional generation benchmarks.
State-of-the-art vision-language-action models catastrophically fail dynamic embodied reasoning due to lexical-kinematic shortcuts, behavioral inertia, and semantic feature collapse caused by architectural bottlenecks, as shown by the new BeTTER benchmark with real-world validation.
ConvFormer3D-TAP classifies six cine CMR views at 96% accuracy using 3D conv tokenization, multiscale attention, and uncertainty-aware multi-clip fusion on 150k sequences.
VAGNet anticipates accidents in dashcam videos using global features from VideoMAE-V2 combined with transformers and graphs, reporting higher average precision and mean time-to-accident on four benchmarks while running more efficiently than prior methods.
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Video Diffusion Models
A diffusion model for video generation extends image architectures with joint image-video training and improved conditional sampling, delivering first large-scale text-to-video results and state-of-the-art performance on video prediction and unconditional generation benchmarks.