Cascaded Boundary Regression for Temporal Action Detection

Temporal action detection in long videos is an important problem. State-of-the-art methods address this problem by applying action classifiers on sliding windows. Although sliding windows may contain an identifiable portion of the actions, they may not necessarily cover the entire action instance, which would lead to inferior performance. We adapt a two-stage temporal action detection pipeline with Cascaded Boundary Regression (CBR) model. Class-agnostic proposals and specific actions are detected respectively in the first and the second stage. CBR uses temporal coordinate regression to refine the temporal boundaries of the sliding windows. The salient aspect of the refinement process is that, inside each stage, the temporal boundaries are adjusted in a cascaded way by feeding the refined windows back to the system for further boundary refinement. We test CBR on THUMOS-14 and TVSeries, and achieve state-of-the-art performance on both datasets. The performance gain is especially remarkable under high IoU thresholds, e.g. map@tIoU=0.5 on THUMOS-14 is improved from 19.0% to 31.0%

Focusing a deterministic single-ion beam

We focus down an ion beam consisting of single 40Ca+ ions to a spot size of a few mum using an einzel-lens. Starting from a segmented linear Paul trap, we have implemented a procedure which allows us to deterministically load a predetermined number of ions by using the potential shaping capabilities of our segmented ion trap. For single-ion loading, an efficiency of 96.7(7)% has been achieved. These ions are then deterministically extracted out of the trap and focused down to a 1sigma-spot radius of (4.6 \pm 1.3)mum at a distance of 257mm from the trap center. Compared to former measurements without ion optics, the einzel-lens is focusing down the single-ion beam by a factor of 12. Due to the small beam divergence and narrow velocity distribution of our ion source, chromatic and spherical aberration at the einzel-lens is vastly reduced, presenting a promising starting point for focusing single ions on their way to a substrate.Comment: 16 pages, 7 figure

BasicTAD: an Astounding RGB-Only Baseline for Temporal Action Detection

Temporal action detection (TAD) is extensively studied in the video understanding community by generally following the object detection pipeline in images. However, complex designs are not uncommon in TAD, such as two-stream feature extraction, multi-stage training, complex temporal modeling, and global context fusion. In this paper, we do not aim to introduce any novel technique for TAD. Instead, we study a simple, straightforward, yet must-known baseline given the current status of complex design and low detection efficiency in TAD. In our simple baseline (termed BasicTAD), we decompose the TAD pipeline into several essential components: data sampling, backbone design, neck construction, and detection head. We extensively investigate the existing techniques in each component for this baseline, and more importantly, perform end-to-end training over the entire pipeline thanks to the simplicity of design. As a result, this simple BasicTAD yields an astounding and real-time RGB-Only baseline very close to the state-of-the-art methods with two-stream inputs. In addition, we further improve the BasicTAD by preserving more temporal and spatial information in network representation (termed as PlusTAD). Empirical results demonstrate that our PlusTAD is very efficient and significantly outperforms the previous methods on the datasets of THUMOS14 and FineAction. Meanwhile, we also perform in-depth visualization and error analysis on our proposed method and try to provide more insights on the TAD problem. Our approach can serve as a strong baseline for future TAD research. The code and model will be released at https://github.com/MCG-NJU/BasicTAD.Comment: Accepted by CVI

Investigation of the aerothermodynamics of hypervelocity reacting flows in the ram accelerator

New diagnostic techniques for measuring the high pressure flow fields associated with high velocity ram accelerator propulsive modes was experimentally investigated. Individual propulsive modes are distinguished by their operating Mach number range and the manner in which the combustion process is initiated and stabilized. Operation of the thermally choked ram accelerator mode begins by injecting the projectile into the accelerator tube at a prescribed entrance velocity by means of a conventional light gas gun. A specially designed obturator, which is used to seal the bore of the gun, plays a key role in the ignition of the propellant gases in the subsonic combustion mode of the ram accelerator. Once ignited, the combustion process travels with the projectile and releases enough heat to thermally choke the flow within several tube diameters behind it, thereby stabilizing a high pressure zone on the rear of the projectile. When the accelerating projectile approaches the Chapman-Jouguet detonation speed of the propellant mixture, the combustion region is observed to move up onto the afterbody of the projectile as the pressure field evolves to a distinctively different form that implies the presence of supersonic combustion processes. Eventually, a high enough Mach number is reached that the ram effect is sufficient to cause the combustion process to occur entirely on the body. Propulsive cycles utilizing on-body heat release can be established either by continuously accelerating the projectile in a single propellant mixture from low initial in-tube Mach numbers (M less than 4) or by injecting the projectile at a speed above the propellant's Chapman-Jouguet detonation speed. The results of experimental and theoretical explorations of ram accelerator gas dynamic phenomena and the effectiveness of the new diagnostic techniques are presented in this report